Method for the diagnosis and prognosis of cancer

ABSTRACT

The present invention provides methods and materials for diagnosing cancer in an individual using a tissue, blood or urine sample from the patient. Specifically, the disclosed method comprises determining the level of one or more metabolite selected from the group consisting of creatine riboside, metabolite 561+, Cortisol sulfate and N-acetylneuraminic acid. The present invention also provides a method for determining the prognosis of a cancer patient by determining the level of one or more metabolite selected from the group consisting of creatine riboside, metabolite 561+, Cortisol sulfate and N-acetylneuraminic acid. Also provided are kits for detecting cancer or determining the prognosis of a cancer patient.

FIELD OF INVENTION

The present invention relates to the use of specific biomarkers in thedetection of cancer and the prediction of the prognosis of cancerpatients.

SUMMARY OF INVENTION

Methods of the present invention relate to the use of specificbiomarkers to detect the presence of cancer in an individual. Thedisclosed methods are also useful for determining the prognosis of anindividual known to have cancer. In particular, methods of the presentinvention may generally be accomplished by determining the levels of oneor more specific biomarkers, disclosed herein, within an individual.Alterations in these levels relative to the levels of the same one ormore biomarkers in individuals known to be free of cancer are indicativeof the presence of cancer.

One embodiment of the present invention is a method for the detection ofcancer, comprising determining the level of at least two compoundsselected from the group consisting of creatine riboside, metabolite561+, cortisol sulfate and N-acetylneuraminic acid, in a sample obtainedfrom an individual, wherein elevated levels of the at least twocompounds indicates the presence of cancer. In one embodiment, themethod comprises determining the level of at least three compoundsselected from the group consisting of creatine riboside, metabolite561+, cortisol sulfate and N-acetylneuraminic acid in a sample obtainedfrom an individual, wherein elevated levels of the at least threecompounds indicates the presence of cancer. In one embodiment the methodcomprises determining the level of creatine riboside, metabolite 561+,cortisol sulfate and N-acetylneuraminic acid in a sample obtained froman individual, wherein elevated levels of all four compounds indicatesthe presence of cancer. In one embodiment, the cancer is lung cancer. Inone embodiment, the cancer comprises adenocarcinoma. In one embodiment,the cancer comprises squamous cell carcinoma. In one embodiment, thesample is body tissue. In one embodiment, the sample is a body fluid. Inone embodiment, the sample is urine. In one embodiment, the sample isselected from the group consisting of blood, serum and plasma.

One embodiment of the present invention is a method for the detection ofcancer comprising determining the level of one or more compoundsselected from the group consisting of creatine riboside and metabolite561+, in a sample from an individual, wherein elevated levels ofcreatine riboside and/or metabolite 561+ indicate the presence ofcancer. In one embodiment, the method comprises determining the levelsof creatine riboside and metabolite 561+, in a sample, wherein elevatedlevels of creatine riboside and metabolite 561+ indicate the presence ofcancer. In one embodiment, the cancer is lung cancer. In one embodiment,the cancer comprises adenocarcinoma. In one embodiment, the cancercomprises squamous cell carcinoma. In one embodiment, the sample is bodytissue. In one embodiment, the sample is a body fluid. In oneembodiment, the sample is urine. In one embodiment, the sample isselected from the group consisting of blood, serum and plasma.

One embodiment of the present invention is a method for the detection oflung cancer comprising determining the level of cortisol sulfate in asample obtained from an individual, wherein an elevated level ofcortisol sulfate indicates the presence of lung cancer. In oneembodiment, the cancer comprises adenocarcinoma. In one embodiment, thecancer comprises squamous cell carcinoma. In one embodiment, the sampleis body tissue. In one embodiment, the sample is a body fluid. In oneembodiment, the sample is urine. In one embodiment, the sample isselected from the group consisting of blood, serum and plasma.

One embodiment of the present invention is a method for the detection oflung cancer, comprising determining the level of N-acetylneuraminic acidin urine from an individual, wherein an elevated level of urinaryN-acetylneuraminic acid indicates the presence of lung cancer. In oneembodiment, the N-acetylneuraminic acid is N-acetylneuraminic acid. Inone embodiment, the cancer comprises adenocarcinoma. In one embodiment,the cancer comprises squamous cell carcinoma.

One embodiment of the present invention is a method for monitoring theefficacy of a cancer treatment, the method comprising:

-   -   a) determining the level of one or more biomarkers selected from        the group consisting of creatine riboside, metabolite 561+,        cortisol sulfate and N-acetylneuraminic acid in a sample patient        having cancer to obtain a pre-treatment level of the one or more        biomarkers;    -   b) administering a cancer treatment to the patient;    -   c) determining the level of the one or more biomarkers of the        present invention in the patient to obtain a post-treatment        level of the one or more biomarkers; and    -   d) comparing the pre-treatment and post-treatment biomarker        levels to determine the efficacy of the treatment.

In one embodiment, the method comprises determining the level of two ormore compounds selected from the group consisting of creatine riboside,metabolite 561+, cortisol sulfate and N-acetylneuraminic acid in thesample. In one embodiment, the method comprises determining the level ofthree or more compounds selected from the group consisting of creatineriboside, metabolite 561+, cortisol sulfate and N-acetylneuraminic acidin the sample. In one embodiment the method comprises determining thelevel of creatine riboside, metabolite 561+, cortisol sulfate andN-acetylneuraminic acid in the sample. In one embodiment, the cancer islung cancer. In one embodiment, the cancer comprises adenocarcinoma. Inone embodiment, the cancer comprises squamous cell carcinoma. In oneembodiment, the sample is body tissue. In one embodiment, the sample isa body fluid. In one embodiment, the sample is urine. In one embodiment,the sample is selected from the group consisting of blood, serum andplasma.

One embodiment of the present invention is a method for predicting theprognosis of an individual having cancer, the method comprisingdetermining the level of at least one biomarker selected from the groupconsisting of creatine riboside, cortisol sulfate, metabolite 561+ andN-acetylneuraminic acid, in a sample from the individual, wherein anelevated level of the at least one biomarker is indicative of theprognosis of the individual. In one embodiment, the method comprisesdetermining the level of two or more compounds selected from the groupconsisting of creatine riboside, metabolite 561+, cortisol sulfate andN-acetylneuraminic acid in the sample. In one embodiment, the methodcomprises determining the level of three or more compounds selected fromthe group consisting of creatine riboside, metabolite 561+, cortisolsulfate and N-acetylneuraminic acid in the sample. In one embodiment themethod comprises determining the level of creatine riboside, metabolite561+, cortisol sulfate and N-acetylneuraminic acid in the sample. In oneembodiment, the cancer is lung cancer. In one embodiment, the cancercomprises adenocarcinoma. In one embodiment, the cancer comprisessquamous cell carcinoma. In one embodiment, the sample is body tissue.In one embodiment, the sample is a body fluid. In one embodiment, thesample is urine. In one embodiment, the sample is selected from thegroup consisting of blood, serum and plasma. In one embodiment, anelevated level of the at least one biomarker indicates a reducedsurvival time relative to a cancer patient in whom the level of the atleast one biomarker is not elevated. In one embodiment, elevated levelsof creatine riboside and metabolite 561+ indicate a reduced survivaltime relative to a cancer patient in whom the levels of creatineriboside and metabolite 561+ are not elevated. In one embodiment,elevated levels of creatine riboside, metabolite 561+, andN-acetylneuraminic acid indicate a reduced survival time relative to acancer patient in whom the levels of creatine riboside, metabolite 561+and N-acetylneuraminic acid are not elevated

BACKGROUND

Lung cancer is the leading cause of cancer deaths in men and women bothin the United States (Jemal A, Simard E P, Dorell C, et al Annual Reportto the Nation on the Status of Cancer, 1975-2009, Featuring the Burdenand Trends in Human Papillomavirus (HPV)-Associated Cancers and HPVVaccination Coverage Levels. J Natl Cancer Inst 2013; Jemal A, Bray F,Center M M, Ferlay J, Ward E, Forman D. Global cancer statistics. CACancer J Clin 2011; 61:69-90) and worldwide (Boyle P L B, ed. The WorldCancer Report 2008. Lyon, France: IARC; 2008). Survival rates remaindismal, with 5-year survival ranging from <5% for distant, to 24% forregional, to 53% for localized disease (Horner M, Ries L A G, Krapcho M,et al. SEER Cancer Statistics Review, 1975-2006. In. Bethesda, Md.:National Cancer Institute; 2009). This substantial survival ratedecrease in advanced disease provides a strong motivation to search forearly diagnostic and prognostic biomarkers.

Current clinically accepted methods for the early detection of lungcancer are limited to spiral CT scanning in smokers between the ages of55 to 74 and a 30 pack year smoking history (Jaklitsch M T, Jacobson FL, Austin J H, et al. The American Association for Thoracic Surgeryguidelines for lung cancer screening using low-dose computed tomographyscans for lung cancer survivors and other high-risk groups. J ThoracCardiovasc Surg 2012; 144:33-8; American Cancer Society. American CancerSociety Guidelines for the Early Detection of Cancer, 2013. However,spiral CT scanning provides a high rate of false positives, namely 96.4%overall and 24% of those with invasive testing (Aberle D R, Adams A M,Berg C D, et al. Reduced lung-cancer mortality with low-dose computedtomographic screening. N Engl J Med 2011; 365:395-409). Also, spiral CTscanning may lead to an attendant increase in lung cancer risk due toradiation exposure (Brenner D J. Radiation risks potentially associatedwith low-dose CT screening of adult smokers for lung cancer. Radiology2004; 231:440-5; Buls N, de Mey J, Covens P, Stadnik T. Health screeningwith CT: prospective assessment of radiation dose and associateddetriment. JBR-BTR 2005; 88:12-6). Thus, a concordant biomarker tobetter identify those who should be screened or undergo invasivediagnostic work-ups is needed. Importantly, while imaging techniquesperform poorly in identifying early stage lung cancer, the use ofmolecular biomarkers provides hope for early detection. However, todate, no molecular biomarker for early stage lung cancer has beenvalidated (Vansteenkiste J, Dooms C, Mascaux C, Nackaerts K. Screeningand early detection of lung cancer. Ann Oncol 2012; 23 Suppl 10:x320-7;Hassanein M, Callison J C, Callaway-Lane C, Aldrich M C, Grogan E L,Massion P P. The state of molecular biomarkers for the early detectionof lung cancer. Cancer Prev Res (Phila) 2012; 5:992-1006).

Several biomarkers are available for the assessment of overall prognosisand for guiding therapy. For example, the KRAS mutation in non-smallcell lung cancer (NSCLC) confers a significantly shorter survival(HR=1.21) in stage IV disease (Johnson M L, Sima C S, Chaft J, et al.Association of KRAS and EGFR mutations with survival in patients withadvanced lung adenocarcinomas. Cancer 2013; 119:356-62). The presence ofan ALK or EGFR mutation indicates a responsive tumor to targetedtherapies and longer survival (Lynch T J, Bell D W, Sordella R, et al.Activating mutations in the epidermal growth factor receptor underlyingresponsiveness of non-small-cell lung cancer to gefitinib. N Engl J Med2004; 350:2129-39; Paez J G, Janne P A, Lee J C, et al. EGFR mutationsin lung cancer: correlation with clinical response to gefitinib therapy.Science 2004; 304:1497-500; Pao W, Miller V, Zakowski M, et al. EGFreceptor gene mutations are common in lung cancers from “never smokers”and are associated with sensitivity of tumors to gefitinib anderlotinib. Proc Natl Acad Sci USA 2004; 101:13306-11; Mok T S, Wu Y L,Thongprasert S, et al. Gefitinib or carboplatin-paclitaxel in pulmonaryadenocarcinoma. N Engl J Med 2009; 361:947-57; Antoniu S A. Crizotinibfor EML4-ALK positive lung adenocarcinoma: a hope for the advanceddisease? Evaluation of Kwak E L, Bang Y J, Camidge D R, et al.Anaplastic lymphoma kinase inhibition in non-small-cell lung cancer. NEngl J Med 2010; 363(18):1693-703. Expert Opin Ther Targets 2011;15:351-3). However, current clinically accepted biomarkers for lungcancer outcomes are based on tumor assays, an invasive approach that canbe limited due to tissue availability.

Urine is gaining increasing interest as a biospecimen for detectingcancer biomarkers (Schmidt C. Urine biomarkers may someday detect evendistant tumors. J Natl Cancer Inst 2009; 101:8-10), notably because itis collected noninvasively, abundant, and requires minimal preparation.Presently, only one urinary cancer biomarker is clinically applied,PCA3, for detecting prostate cancer (Groskopf J, Aubin S M, Deras I L,et al. APTIMA PCA3 molecular urine test: development of a method to aidin the diagnosis of prostate cancer. Clin Chem 2006; 52:1089-95).However, no clinically applied biomarkers exist for lung cancer, butpromising urinary biomarkers include modified nucleosides (Henneges C,Bullinger D, Fux R, et al. Prediction of breast cancer by profiling ofurinary RNA metabolites using Support Vector Machine-based featureselection. BMC Cancer 2009; 9:104; Hsu W Y, Chen W T, Lin W D, et al.Analysis of urinary nucleosides as potential tumor markers in humancolorectal cancer by high performance liquid chromatography/electrosprayionization tandem mass spectrometry. Clin Chim Acta 2009; 402:31-7; JengL B, Lo W Y, Hsu W Y, et al. Analysis of urinary nucleosides as helpertumor markers in hepatocellular carcinoma diagnosis. Rapid Commun MassSpectrom 2009; 23:1543-9; Manjula S, Aroor A R, Raja A, Rao S, Rao A.Urinary excretion of pseudouridine in patients with brain tumours. ActaOncol 1993; 32:311-4; Sasco A J, Rey F, Reynaud C, Bobin J Y, Clavel M,Niveleau A. Breast cancer prognostic significance of some modifiedurinary nucleosides. Cancer Lett 1996; 108:157-62; Vreken P, Tavenier P.Urinary excretion of six modified nucleosides by patients with breastcarcinoma Ann Clin Biochem 1987; 24 (Pt 6):598-603; Xu G, Di Stefano C,Liebich H M, Zhang Y, Lu P. Reversed-phase high-performance liquidchromatographic investigation of urinary normal and modified nucleosidesof cancer patients. J Chromatogr B Biomed Sci Appl 1999; 732:307-13; XuG, Schmid H R, Lu X, Liebich H M, Lu P. Excretion pattern investigationof urinary normal and modified nucleosides of breast cancer patients byRP-HPLC and factor analysis method. Biomed Chromatogr 2000; 14:459-63),where high levels indicate an increased RNA turnover and degradation.Clinical trials evaluating the utility of these nucleotides in variousdiseases, including cancer, are ongoing.

Metabolomics is an increasingly popular approach for uncovering newbiomarkers for diagnosis (Kim Y S, Maruvada P, Milner J A. Metabolomicsin biomarker discovery: future uses for cancer prevention. Future Oncol2008; 4:93-102; Kind T, Tolstikov V, Fiehn O, Weiss R H. A comprehensiveurinary metabolomic approach for identifying kidney cancerr. AnalBiochem 2007; 363:185-95; Matsumura K, Opiekun M, Oka H, et al. Urinaryvolatile compounds as biomarkers for lung cancer: a proof of principlestudy using odor signatures in mouse models of lung cancer. PLoS One2010; 5:e8819; Sreekumar A, Poisson L M, Rajendiran T M, et al.Metabolomic profiles delineate potential role for sarcosine in prostatecancer progression. Nature 2009; 457:910-4; Yang Q, Shi X, Wang Y, etal. Urinary metabonomic study of lung cancer by a fully automatichyphenated hydrophilic interaction/RPLC-MS system. J Sep Sci 2010;33:1495-503; Yuan J M, Gao Y T, Murphy S E, et al. Urinary levels ofcigarette smoke constituent metabolites are prospectively associatedwith lung cancer development in smokers. Cancer Res 2011; 71:6749-57)and customized treatment (Fan T W, Lane A N, Higashi R M. The promise ofmetabolomics in cancer molecular therapeutics. Curr Opin Mol Ther 2004;6:584-92), and for evaluating characteristics of metastatic cells(Mountford C E, Wright L C, Holmes K T, Mackinnon W B, Gregory P, Fox RM. High-resolution proton nuclear magnetic resonance analysis ofmetastatic cancer cells. Science 1984; 226:1415-8) and carcinogenictobacco-smoke constituents (Church T R, Anderson K E, Caporaso N E, etal. A prospectively measured serum biomarker for a tobacco-specificcarcinogen and lung cancer in smokers. Cancer Epidemiol Biomarkers Prev2009; 18:260-6; Hecht S S, Hatsukami D K, Bonilla L E, Hochalter J B.Quantitation of 4-oxo-4-(3-pyridyl)butanoic acid and enantiomers of4-hydroxy-4-(3-pyridyl)butanoic acid in human urine: A substantialpathway of nicotine metabolism. Chem Res Toxicol 1999; 12:172-9; Hecht SS, Murphy S E, Stepanov I, Nelson H H, Yuan J M. Tobacco smokebiomarkers and cancer risk among male smokers in the Shanghai CohortStudy. Cancer Lett 201). However, most studies suffer from limitedsample sizes, quality control, and lack of technical and biologicalvalidation. Metabolomic studies are unique and powerful because theymeasure both exogenous (e.g. cigarette smoke constituents) andendogenous molecules from cellular processes reacting to different typesof exposures. Among methods for measuring metabolites, mass spectrometryis very sensitive and requires only small quantities of biospecimens(Griffin J L. The Cinderella story of metabolic profiling: doesmetabolomics get to go to the functional genomics ball? Philos Trans RSoc Lond B Biol Sci 2006; 361:147-61). A recent study has provided proofof principle evidence for the use of metabolomics in smokers thatdemonstrates the reliability and reproducibility of the assay, and theability to distinguish levels and smoking status (Hsu P C, Zhou B, ZhaoY, et al. Feasibility of identifying the tobacco-related globalmetabolome in blood by UPLC-QTOF-MS. J Proteome Res 2012).

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1. Lung cancer staging staging system. (A) Definitions used tostage tumors. (B) Anatomic stage and prognostic groups.

FIG. 2. Quality control assessment in the training set. A)Multidimensional scaling (1—Pearson's Correlation) as the distancemetric was used for unsupervised clustering of ESI+ (left panel) andESI− (right panel) data. Four controls were used to ensure the qualityof the run: blanks (green asterisk), pooled samples (red triangles),MetMix mass spectrometry standards (blue squares), and nicotinemetabolite standards diluted in water (orange diamonds). Urinecollections from cancer patients and healthy controls are shown in blackdots. B) Distribution of correlation coefficients in duplicate samples.Correlation coefficients were calculated between duplicate samples runin both ESI+(left) and ESI− (right) modes. Correlations were calculatedbefore retention time alignment for duplicate samples (N=254 pairs) andfor randomly selected pairs (N=2500 pairs). The distributions of thesecorrelations show that duplicate samples have very similar metabolicprofiles, as expected. C) Distribution of coefficients of variation(CVs) within each sample type demonstrates low CVs for the qualitycontrol samples when compared to lung cancer cases and healthy controls(P<2E-6).

FIG. 3. Abundances of three nicotine metabolites (cotinine,nicotine-N′-oxide, and trans-3′-hydroxycotinine), stratified by smokingstatus, indicating correlation between the self-reported smoking statusand nicotine metabolites presence and abundance in the urine.

FIG. 4. Differences in abundance and validation of signals that were topcontributors in the classification of patients as lung cancer or healthycontrols groups. Untargeted and MSTUS normalized UPLC-MS abundances(mean and standard of the mean (SEM)) are depicted for A) the trainingset containing 469 cases and 536 controls, B) the validation setcomprising 80 cases and 78 controls. Quantitated UPLC-MS/MS abundances(mean and SEM) in C) a subset of the training set containing 92 casesand 106 controls, D) a matched tissue set containing 48 stage I tumorsand 48 adjacent non-tumor samples. E) Absolute concentration ranges ofidentified metabolites with available pure standards forN-acetylneuraminic acid and cortisol sulfate are shown for cases andcontrols. F) Intraclass correlation coefficients were calculated for thequantitated subset of 198 samples, where measurements were obtained attwo time points over two years apart. FC=fold change.

FIG. 5. MS-MS validation in comparison to commercially available andsynthesized standards of A) Creatine riboside, B) Cortisol sulfate, andC) N-acetyl neuraminic acid. D) MS-MS of un-indentified metabolite561.3432+. E) Fragmentation pattern depiction of the novel and in-housesynthesized compound creatine riboside.

FIG. 6. NMR confirmation of creatine riboside structure. ¹H-¹³C HMBCspectrum of the reaction mixture between ribose and creatine in dmso-d⁶.

FIG. 7. A) Creatine levels (quantitated abundances) are elevated in thetumors of the tissue sample set (48 matched tumor/adjacent non-tumorsamples) B) Correlation analysis between creatine riboside and creatinequantitated in tumor tissue samples.

FIG. 8. Association of top four metabolites with lung cancer diagnosis.Signal abundances are dichotomized using the third quartile of healthycontrol abundances as a cutoff. A) Logistic regression results withreported false discovery rate (FDR) values based on Benjamini-Hochbergmethod. B) ROC analysis of individual metabolites and their combinationin all cases, and in stage I-II cases.

FIG. 9. Relative abundances of the top four diagnostic and prognosticbiomarkers stratified by cigarettes per day (cpd) of self-reportedsmoking 48 hours prior to the interview in the training set (78 lungcancer cases and 48 population controls). There were no statisticallysignificant differences of abundances observed across the strata.

FIG. 10. Diurnal effects on urine metabolites in the training set.Distribution plots depicting relative signal abundances across urinecollection times (a—am, p—pm) in A) lung cancer cases and B) populationcontrols.

FIG. 11. Kaplan-Meier survival estimates are depicted for top fourbiomarkers. Metabolites significantly associated with prognosis in A)all lung cancer patients and B) stage I-II lung cancer patients areshown. The P values reported in the Kaplan-Meier plots reflect themaximum likelihood estimates generated using a univariate Cox model,taking into account left truncation (the lag time between diagnosis andtime of urine collection). C) Combination of putative diagnostic andprognostic biomarkers is shown for all cases, and stage I-II cases. Onlymetabolites that showed statistically significant associations withsurvival, independent of clinical factors, were combined. As such,scores derived for cortisol sulfate, N-acetylneuraminic acid, creatineriboside and 561+ were combined for the analysis of all cases; creatineriboside and 561+ scores were combined for the analysis of stage I-IIcases.

FIG. 12. Survival analysis stratified by stage in training set samples(N=469). Kaplan-Meier survival plots A) and Cox proportional hazardsregression analysis, taking in to account left truncation of the topfour diagnostic and prognostic biomarkers B).

FIG. 13. Survival analysis of top four signals in the quantitation setcontaining representative 198 samples (92 cases, 106 controls),quantitated by UPLC-MS/MS. A) Kaplan Meier survival plots of individualmetabolites and B) their combination. C) Cox proportional hazardsregression results are depicted for all cases in the representativequantitation set (N=92).

FIG. 14. Overlap between signals that are predictive of lung cancerstatus (using random forests) in the training set, in samples stratifiedby race and gender A), and smoking status B).

FIG. 15. Principal Component Analysis (PCA) of colon tumor and non-tumortissue samples and quality controls (blank, metmix and cocktailcontaining internal standards).

FIG. 16. Box plots of the relative levels of creatine riboside and NANAin 40 colon cancer matched tumor/non-tumor tissue pairs.

FIG. 17. Logistic regression analysis in liver cancer (Top) and prostatecancer (Bottom).

FIG. 18. Box plots depicting levels of metabolites in (A) liver cancerand (B) prostate cancer compared to their respective populationcontrols. P-values depicted are results of Wilcoxon analysis.

DETAILED DESCRIPTION OF THE INVENTION

Lung cancer remains the leading cause of cancer-related death in bothmen and women worldwide. The current clinically accepted method forearly detection of lung cancer (i.e., spiral CT scanning) is expensive,exposes the patient to high levels of radiation and its use is limitedto smokers within a certain age range. Moreover, current testingprocedures result in a high rate of false positives. Thus, what isneeded are methods for diagnosing cancer, and in particular lung cancer,that are less expensive, safer and more accurate. The present inventionprovides such methods. In particular, the present invention relates to anovel method for detecting cancer by detecting the level of specificbiomarkers in an individual. Such a method is inexpensive, requires onlya small sample from the patient and can be performed quickly and safely.

Before the present invention is further described, it is to beunderstood that this invention is not limited to particular embodimentsdescribed, as such may, of course, vary. It is also to be understoodthat the terminology used herein is for the purpose of describingparticular embodiments only, and is not intended to be limiting, sincethe scope of the present invention will be limited only by the claims.

It is further noted that the claims may be drafted to exclude anyoptional element. As such, this statement is intended to serve asantecedent basis for use of such exclusive terminology as “solely,”“only” and the like in connection with the recitation of claim elements,or use of a “negative” limitation.

The publications discussed herein are provided solely for theirdisclosure prior to the filing date of the present application. Nothingherein is to be construed as an admission that the present invention isnot entitled to antedate such publication by virtue of prior invention.Further, the dates of publication provided may be different from theactual publication dates, which may need to be independently confirmed.All publications mentioned herein are incorporated herein by referenceto disclose and describe the methods and/or materials in connection withwhich the publications are cited.

It is appreciated that certain features of the invention, which are, forclarity, described in the context of separate embodiments, may also beprovided in combination in a single embodiment. Conversely, variousfeatures of the invention, which are, for brevity, described in thecontext of a single embodiment, may also be provided separately or inany suitable sub-combination. All combinations of the embodiments arespecifically embraced by the present invention and are disclosed hereinjust as if each and every combination was individually and explicitlydisclosed. In addition, all sub-combinations are also specificallyembraced by the present invention and are disclosed herein just as ifeach and every such sub-combination was individually and explicitlydisclosed herein.

Unless defined otherwise, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which this invention belongs. Although any methods andmaterials similar or equivalent to those described herein can also beused in the practice or testing of the present invention, the preferredmethods and materials are now described.

A method of the present invention may generally be accomplished bydetermining the levels of one or more specific biomarkers, disclosedherein, within an individual, and determining if such levels areelevated compared to the levels of corresponding biomarkers in a samplefrom an individual known to be free of cancer. Determining the level ofbiomarkers of the present invention may also be referred to asdetermining the signature of the individual. As used herein, a signaturerefers to the levels of one or more cancer-related biomarkers of thepresent invention. The inventors have discovered that alterations ofthese levels relative to the levels of the same one or more biomarkersin individuals known to be free of cancer are indicative of the presenceof cancer.

It should be understood that as used herein, the term “a” entity or “an”entity refers to one or more of that entity. For example, a nucleic acidmolecule refers to one or more nucleic acid molecules. As such, theterms “a”, “an”, “one or more” and “at least one” can be usedinterchangeably. Similarly the terms “comprising”, “including” and“having” can be used interchangeably.

As used herein, the terms individual, subject, patient, and the like,are meant to encompass any mammal capable of developing cancer, with apreferred mammal being a human. The terms individual, subject, andpatient by themselves do not denote a particular age, sex, race, and thelike. Thus, individuals of any age, whether male or female, are intendedto be covered by the present disclosure. Likewise, the methods of thepresent invention can be applied to any race of human, including, forexample, Caucasian (white), African-American (black), Native American,Native Hawaiian, Hispanic, Latino, Asian, and European. In someembodiments of the present invention, such characteristics may besignificant. In such cases, the significant characteristic(s) (e.g.,age, sex, race, etc.) will be indicated.

According to the present invention, the term individual encompasses bothhuman and non-human animals. Suitable non-human animals to test forcancer include, but are not limited to companion animals (i.e. pets),food animals, work animals, or zoo animals. Preferred animals include,but are not limited to, cats, dogs, horses, ferrets and other Mustelids,cattle, sheep, swine, and rodents. More preferred animals include cats,dogs, horses and other companion animals, with cats, dogs and horsesbeing even more preferred. As used herein, the term “companion animal”refers to any animal which a human regards as a pet. As used herein, acat refers to any member of the cat family (i.e., Felidae), includingdomestic cats, wild cats and zoo cats. Examples of cats include, but arenot limited to, domestic cats, lions, tigers, leopards, panthers,cougars, bobcats, lynx, jaguars, cheetahs, and servals. A preferred catis a domestic cat. As used herein, a dog refers to any member of thefamily Canidae, including, but not limited to, domestic dogs, wild dogs,foxes, wolves, jackals, and coyotes and other members of the familyCanidae. A preferred dog is a domestic dog. As used herein, a horserefers to any member of the family Equidae. An equid is a hoofed mammaland includes, but is not limited to, domestic horses and wild horses,such as, horses, asses, donkeys, and zebras. Preferred horses includedomestic horses, including race horses.

The individual being tested may or may not be suspected of havingcancer. It will be appreciated by those skilled in the art that someindividuals are at higher risk than other individuals for developingcancer. For example, it is known that certain activities andenvironments increase the risk of developing cancer. Examples of suchactivities and environments included, but are not limited to smoking,exposure to second-hand smoke, exposure to asbestos, sun-tanning,exposure to radon gas, excessive alcohol consumption, exposure to highlevels of radiation, and exposure to chemicals known to be carcinogenic.Thus, in one embodiment, the individual is known to engage in one ormore activities that increases the risk for developing cancer. In oneembodiment the individual has an increased risk of developing cancer.

Additionally, some individuals are at higher risk for developing cancerdue to mutations in genes encoding proteins that act as tumor suppressorproteins. Mutations in these proteins render these proteins inefficientor ineffective resulting in the development of cancer. It is understoodby those skilled in the art that a variant gene sequence may be referredto as an allele and that certain alleles are known to be associated withdeveloping cancer. Examples of genes known to be associated with thedevelopment of cancer include, but are not limited to P53, APC, RB1,BRCA1, BRCA2, EGFR, KRAS, ALK, RET, KIT, and MET. In one embodiment, theindividual carries a mutation or allele that is known to be associatedwith the development of cancer.

As used herein, cancer refers to diseases in which abnormal cells dividewithout the appropriate control of cell division and senescence. In somecancers, the cells are able to invade tissues other than those fromwhich the original cancer cells arose. In some cancers, cancer cells mayspread to other parts of the body through the blood and lymph systems.Thus, cancers are usually named for the organ or type of cell in whichthey start. For example, a cancer that originates in the colon is calledcolon cancer; cancer that originates in melanocytes of the skin iscalled melanoma, etc. As used herein, cancer may refer to carcinomas,sarcomas, adenocarcinomas, lymphomas, leukemias, etc., including solidand lymphoid cancers, gastric, kidney cancer, breast cancer, lung cancer(including non-small cell and small cell lung cancer), bladder cancer,colon cancer, ovarian cancer, prostate cancer, pancreas cancer, stomachcancer, brain cancer, head and neck cancers, skin cancer, uterinecancer, testicular cancer, esophageal cancer, liver cancer (includinghepatocarcinoma), lymphoma, including non-Hodgkin's lymphomas (e.g.,Burkitt's, Small Cell, and Large Cell lymphomas) and Hodgkin's lymphoma,leukemia, and multiple myeloma. In one embodiment, the cancer is lungcancer. In one embodiment, the cancer is adenocarcinoma.

It is understood in the art that early detection of cancer is importantin order to improve the odds of survival. For example, with regard tolung cancer, the 5 year survival rate is 50% when the disease is caughtin the early stages. Staging of a cancer is a classification systembased on such things as the involvement of lymph nodes and metastasis ofthe tumor to secondary sites. For example, a new tumor starts out inStage 0 but as it grows and spreads it progresses through Stages 1-IV.One Example of a staging system is shown in FIGS. 1A and 1B. With regardto the present invention, staging of the cancers disclosed herein wasperformed according to the method of Edge S., et al., AJCC CancerStaging Manual. 7^(th) ed: Springer-Verlag; 2010, which is incorporatedin it's entirety. As used herein, early stages of cancer, early cancer,early disease, and the like, refer to a cancer that is in Stage 0, StageI or Stage II. In one embodiment, the individual being tested issuspected of being in the early stages of cancer.

A biomarker may be described as a characteristic that is objectivelymeasured and evaluated as an indicator of normal biologic processes,pathogenic processes, or pharmacologic responses to a therapeuticintervention (Biomarkers Definitions Working Group. Biomarkers andsurrogate endpoints: preferred definitions and conceptual framework.Clin Pharmacol Ther. 2001 March; 69(3):89-95.) As used herein, the termsbiomarker, cancer-marker, cancer-associated biomarker, cancer-associatedantigen, and the like, refer to a molecule, the level of which isaltered in an individual having cancer relative to the level of the samebiomarker in an individual known to be free of cancer. A cancerbiomarker may be any molecule for which the level of the molecule in anindividual having cancer is altered in comparison to the level observedin an individual free of cancer. Examples of such molecules includenucleic acid molecules (i.e., RNA and DNA), proteins, lipids,carbohydrates, amino acids, nucleotides and combinations thereof.Preferred biomarkers are those for which the levels of the biomarker maybe determined in a quick and efficient manner.

With regard to the biomarkers disclosed herein, the inventors havediscovered that the levels of one or more such biomarkers are elevated(i.e., increased) in individuals having cancer. As used herein, the termelevated refers to an increased level of a biomarker in an individualhaving cancer compared to the level of biomarker observed in anindividual known to be free of cancer (the normal level). According tothe present invention, the normal level of a biomarker is the levelobserved in a) a population of individuals known to be free of cancer;and/or 2) the level of biomarker observed in the individual beingtested, wherein the level was determined at a time when the individualwas known to be free of cancer. A normal level may also be referred toas a base level, control level or reference level.

In one embodiment, the level of at least one biomarker in an individualhaving cancer is at least 1.2-fold, at least 1.4-fold, at least1.6-fold, at least 1.8-fold, at least 2-fold, at least 3-fold, at least4-fold, at least 5-fold, at least 10-fold, at least 15-fold, at least20-fold, at least 25-fold, at least 50-fold or at least 100-fold greaterthan the normal level of the at least one biomarker. In one embodiment,the level of at least one biomarker in an individual having cancer iselevated by at least 20%, at least 30%, at least 40%, at least 50%, atleast 100%, at least 200%, at least 300%, at least 400%, at least 500%at least 1000%, at least 2000%, at least 5000% or at least 10,000% overthe normal level of the at least one biomarker.

The present inventors have discovered that elevated levels of specificbiomarkers, either alone or in combination, may be used to identifyindividuals having cancer. Thus, one embodiment of the present inventionis a method for identifying an individual having cancer, comprisingdetermining the level of at least two biomarkers of the presentinvention, wherein elevated levels of the at least two biomarkersindicates the presence of cancer. Examples of useful biomarkers foridentifying individuals having cancer include, but are not limited to,creatine riboside, metabolite 561+, cortisol sulfate andN-acetylneuraminic acid (NANA).

The structures of N-acetylneuraminic acid and cortisol sulfate are shownbelow and are also described in the database and ontology of ChemicalEntities of Biological Interest (ChEBI) of the European BioinformaticsInstitute (EBI), which is part of the European Molecular BiologyLaboratory.

Creatine riboside (formula=C9H17N3O6) is a novel compound, the structureof which is shown in FIG. 5E. In particular, FIG. 5E shows the production mass spectra obtained by monitoring characteristic fragmentationpatterns in multiple reaction monitoring (MRM) mode. The chemicalstructures illustrated in FIG. 5E were determined according to themethods disclosed in Example 1.

Metabolite 561+ is a glucoronidated lipid, the MS-MS fragmentationpatterns of which are shown in FIG. 5D. The chemical and physicalcharacteristics of compound 561+ were determined as described in Example1.

One embodiment of the present invention is a method for detecting thepresence of cancer in an individual, comprising determining the level ofat least two biomarkers selected from the group consisting of creatineriboside, metabolite 561+, cortisol sulfate and N-acetylneuraminic acid,wherein elevated levels of the at least two biomarkers indicates thepresence of cancer. In some embodiments, assays using additionalbiomarkers may lead to improved rates of detection and diagnosis ofcancer. Thus, one embodiment is a method for detecting the presence ofcancer in an individual, comprising determining the level of at leastthree biomarkers selected from the group consisting of creatineriboside, metabolite 561+, cortisol sulfate and N-acetylneuraminic acid,wherein elevated levels of the at least three biomarkers indicates thepresence of cancer. One embodiment is a method for detecting thepresence of cancer in an individual, comprising determining the level ofcreatine riboside, metabolite 561+, cortisol sulfate andN-acetylneuraminic acid, wherein elevated levels creatine riboside,metabolite 561+, cortisol sulfate and N-acetylneuraminic acid indicatesthe presence of cancer. In one embodiment, the cancer is colon cancer.In one embodiment, the cancer is lung cancer. In one embodiment thecancer is adenocarcinoma. In one embodiment, the cancer is squamous cellcarcinoma.

In one embodiment of the present invention, the level of one or morebiomarkers is determined from a sample obtained, or collected, from anindividual to be tested for the presence of cancer. A sample is anyspecimen obtained from the individual that can be used to measure thelevel one or more biomarkers. In a particular embodiment, a sample isany specimen obtained from the individual that can be used to measurethe level one or more biomarkers selected from the group consisting ofcreatine riboside, metabolite 561+, cortisol sulfate andN-acetylneuraminic acid. Examples of useful samples include body fluidsand tissue from an individual being tested. A preferred sample is abodily fluid. Those skilled in the art can readily identify appropriatetypes of samples.

Urine, blood plasma and blood serum are particularly suitable as thesample. Blood plasma (“plasma”) or blood serum (“serum”) may be obtainedusing standard techniques know to those skilled in the art. Urinesamples may also be collected from animals by methods known in the art,including, for example, collecting while the individual is voiding,collecting by catheterization, or by cystocentesis. Urine, plasma, orserum samples may be refrigerated or frozen before assay, but arepreferably assayed soon after collection. In one embodiment, the levelof one or more biomarkers is determined from a plasma or serum sample.In one embodiment, the level of one or more biomarkers is determinedfrom a urine sample.

Although not necessary for the present invention, the sample may bepre-treated as desired prior to determining the level of biomarkerspresent in the sample. For example, the sample can be filtered, treatedchemically or enzymatically or, if the sample is urine, it may benormalized to a desired specific gravity. Normalizing the sample byappropriate dilution methods known in the art permits quantification ofbiomarkers independent of the concentration (e.g. specific gravity) ofthe sample. Any desired specific gravity can be readily selected bythose skilled in the art. Additionally, the level of a biomarker presentin a sample may be normalized to another compound present in the sample,such as, for example, hemoglobin level, packed red cell volume orcreatinine Appropriate methods for normalizing a sample are known tothose skilled in the art.

As has been discussed, methods of the present invention rely ondetermining the level of biomarkers. As used herein, the terms“determine,” “determine the level of a biomarker,” “determine the amountof a biomarker,” “determine the biomarker level,” and the like are meantto encompass any technique which can be used to detect or measure thepresence or level of one or more biomarkers. Such techniques may givequalitative or quantitative results. Biomarker levels can be determinedby detecting the entire biomarker molecule or by detecting fragments,degradation products or reaction products that are characteristic of thebiomarker molecule. The terms determining, measuring or taking ameasurement refer to a quantitative or qualitative determination of aproperty of an entity, for example, quantifying the amount orconcentration of a molecule or the activity level of a molecule. Theterm concentration or level can refer to an absolute or relativequantity. For example, the level of a biomarker may be reported as aconcentration (e.g., ug/ml), it may be reported relative to anothervalue such as a normal value (e.g., 3-fold higher than normal), or itmay be reported as a ratio relative to a second molecule (e.g., abiomarker/creatinine ratio of 1.6). Measuring a molecule may alsoinclude determining the absence or presence of the molecule in a sample.

Any known method of detecting or measuring the level of a biomarker canbe used to practice the present invention, so long as the method detectsthe presence, absence, or level or concentration of the biomarker.Examples of such methods include, but are not limited to, bindingassays, such as an immunological detection assays and non-binding assays(e.g., enzymatic detection assays or assays that detect physicalcharacteristics such as mass).

In a binding assay, the sample to be tested for the presence, absence orlevel of a biomarker is contacted with a binding molecule such as, forexample, an antibody. As used herein, the term contact, contacted,contacting, and the like, refers to the introduction of a sampleputatively containing a biomarker to a compound that binds to thebiomarker. One example of a biomarker-binding compound is an antibodythat selectively binds to the biomarker. However, other molecules thatbind to the biomarker may also be used. For example, if the biomarker isa ligand, a receptor to which ligand binds can be used as abiomarker-binding compound in assays of the present invention.Appropriate binding molecules for the biomarkers disclosed herein may bedetermined by those skilled in the art.

In a binding assay, such as an immunological assay, when a biomarker ispresent in the sample, a biomarker-binding compound complex is formed.Such complex formation refers to the ability of a biomarker-bindingcompound to selectively bind to the biomarker in order to form a stablecomplex that can be detected. As used herein, the terms selectively,selective, specific, and the like, indicate the biomarker-bindingcompound has a greater affinity for the biomarker than it does formolecules that are unrelated to the biomarker. More specifically, theterms selectively, selective, specific, and the like indicate that theaffinity of the biomarker-binding compound for a biomarker isstatistically significantly higher than its affinity for a negativecontrol (e.g., an unrelated molecule, such as, for example, albumin) asmeasured using a standard assay (e.g., ELISA). Detection of the complexcan be qualitative, quantitative, or semi-quantitative. Conditions forallowing selective binding and complex formation (e.g., appropriateconcentrations, buffers, temperatures, reaction times) as well asmethods to optimize such conditions are known to those skilled in theart. Binding can be measured using a variety of methods standard in theart including, but not limited to, enzyme immunoassays (e.g., ELISA),immunoprecipitations, immunoblot assays and other immunoassays asdescribed, for example, in Sambrook et al., supra, and Harlow, et al.,supra. These references also provide examples of complex formationconditions.

In one embodiment, the biomarker/binding-compound complex also referredto herein as the B/BC complex or simply as the complex, can be formed insolution. In another embodiment, the complex can be formed while thebiomarker-binding compound is immobilized on (e.g., coated onto) asubstrate. Immobilization techniques are known to those skilled in theart. Suitable substrate materials include, but are not limited to,plastic, glass, gel, celluloid, fabric, paper, and particulatematerials. Examples of substrate materials include, but are not limitedto, latex, polystyrene, nylon, nitrocellulose, agarose, cotton, PVDF(polyvinylidene-fluoride), and magnetic resin. Suitable shapes forsubstrate material include, but are not limited to, a well (e.g.,microtiter dish well), a microtiter plate, a dipstick, a strip, a bead,a lateral flow apparatus, a membrane, a filter, a tube, a dish, acelluloid-type matrix, a magnetic particle, and other particulates.Particularly preferred substrates include, for example, an ELISA plate,a dipstick, an immunodot strip, a radioimmunoassay plate, an agarosebead, a plastic bead, a latex bead, a sponge, a cotton thread, a plasticchip, an immunoblot membrane, an immunoblot paper and a flow-throughmembrane. In one embodiment, a substrate, such as a particulate, caninclude a detectable marker. For descriptions of examples of substratematerials, see, for example, Kemeny, D. M. (1991) A Practical Guide toELISA, Pergamon Press, Elmsford, N.Y. pp 33-44, and Price, C. andNewman, D. eds. Principles and Practice of Immunoassay, 2nd edition(1997) Stockton Press, NY, N.Y., both of which are incorporated hereinby reference in their entirety.

In one embodiment, a biomarker-binding compound is immobilized on asubstrate, such as the well of a microtiter dish, a dipstick, animmunodot strip, or a lateral flow apparatus. A sample collected from anindividual is applied to the substrate and incubated under conditionssuitable (i.e., sufficient) to allow the formation of a complex betweenthe binding compound and any biomarker present in the sample.

In accordance with the present invention, once formed, the complex isthen detected. As used herein, the terms “detecting the complex”,“detecting complex formation” and the like refer to identifying thepresence of biomarker-binding compound complexed to a biomarker of thepresent invention. If complexes are formed, the amount of complexesformed can, but need not be, quantified. Complex formation, or selectivebinding between a biomarker and a biomarker-binding compound, can bemeasured (i.e., detected, determined) using a variety of methodsstandard in the art (see, for example, Sambrook et al. supra.), examplesof which are disclosed herein. A complex can be detected in a variety ofways including, but not limited to use of one or more of the followingassays: an enzyme-linked immunoassay, a competitive enzyme-linkedimmunoassay, a radioimmunoassay, a fluorescence immunoassay, achemiluminescent assay, a lateral flow assay, a flow-through assay, anagglutination assay, a particulate-based assay (e.g., using particulatessuch as, but not limited to, magnetic particles or plastic polymers,such as latex or polystyrene beads), an immunoprecipitation assay, aBIACORE™ assay (e.g., using colloidal gold), an immunodot assay (e.g.,CMG's Immunodot System, Fribourg, Switzerland), and an immunoblot assay(e.g., a western blot), an phosphorescence assay, a flow-through assay,a chromatography assay, a PAGE-based assay, a surface plasmon resonanceassay, a spectrophotometric assay, a particulate-based assay, and anelectronic sensory assay. Such assays are well known to those skilled inthe art. Some assays, such as agglutination, particulate separation, andimmunoprecipitation, can be observed visually (e.g., either by eye or bya machines, such as a densitometer or spectrophotometer) without theneed for a detectable marker.

In other assays, conjugation (i.e., attachment) of a detectable markerto the biomarker-binding compound or to a reagent that selectively bindsto the biomarker-binding compound aids in detecting complex formation. Adetectable marker may be conjugated to the biomarker-binding compound,or reagent, at a site that does not interfere with ability of thecompound to bind the biomarker. Methods of conjugation are known tothose of skill in the art. Examples of detectable markers include, butare not limited to, a radioactive label, a fluorescent label, achemiluminescent label, a chromophoric label, an enzyme label, aphosphorescent label, an electronic label; a metal sol label, a coloredbead, a physical label, or a ligand. A ligand refers to a molecule thatbinds selectively to another molecule. Preferred detectable markersinclude, but are not limited to, fluorescein, a radioisotope, aphosphatase (e.g., alkaline phosphatase), biotin, avidin, a peroxidase(e.g., horseradish peroxidase), beta-galactosidase, and biotin-relatedcompounds or avidin-related compounds (e.g., streptavidin or IMMUNOPURE™NeutrAvidin).

Means of detecting such markers are well known to those of skill in theart. Thus, for example, radiolabels may be detected using photographicfilm or scintillation counters; fluorescent markers may be detectedusing a photodetector to detect emitted light. Enzymatic markers aretypically detected by providing the enzyme with a substrate anddetecting the reaction product produced by the action of the enzyme onthe substrate, and colorimetric markers are detected by simplyvisualizing the colored label.

In one embodiment, a biomarker/binding compound complex can be detectedby contacting a sample with an antibody specific for the bindingcompound, wherein the antibody is conjugated to a detectable marker. Adetectable marker can also be conjugated to an anti-biomarker antibody,or other binding compound. Preferred detectable markers include, but arenot limited to, fluorescein, a radioisotope, a phosphatase (e.g.,alkaline phosphatase), biotin, avidin, a peroxidase (e.g., horseradishperoxidase), beta-galactosidase, and biotin-related compounds oravidin-related compounds (e.g., streptavidin or IMMUNOPURE™NeutrAvidin).

In another embodiment, a complex is detected by contacting the complexwith an indicator molecule. Suitable indicator molecules includemolecules that can bind to the B/BC complex or to the biomarker itself.As such, an indicator molecule can comprise, for example, abiomarker-binding reagent, such as an antibody. Examples of indicatormolecules that are antibodies include, for example, antibodies reactivewith the antibodies from species of animal in which the anti-biomarkerantibodies are produced. An indicator molecule itself can be attached toa detectable marker of the present invention. For example, an antibodycan be conjugated to biotin, horseradish peroxidase, alkalinephosphatase or fluorescein.

The present invention can further comprise one or more layers and/ortypes of secondary molecules or other binding molecules capable ofdetecting the presence of an indicator molecule. For example, anuntagged (i.e., not conjugated to a detectable marker) secondaryantibody that selectively binds to an indicator molecule can be bound toa tagged (i.e., conjugated to a detectable marker) tertiary antibodythat selectively binds to the secondary antibody. Suitable secondaryantibodies, tertiary antibodies and other secondary or tertiarymolecules can be readily selected by those skilled in the art. Preferredtertiary molecules can also be selected by those skilled in the artbased upon the characteristics of the secondary molecule. The samestrategy can be applied for subsequent layers.

Preferably, the indicator molecule is conjugated to a detectable marker.A developing agent is added, if required, and the substrate is submittedto a detection device for analysis. In some protocols, washing steps areadded after one or both complex formation steps in order to removeexcess reagents. If such steps are used, they involve conditions knownto those skilled in the art such that excess reagents are removed butthe complex is retained.

One embodiment of the present invention involves the use of a lateralflow assay, examples of which are described in U.S. Pat. No. 5,424,193,issued Jun. 13, 1995, to Pronovost et al.; U.S. Pat. No. 5,415,994,issued May 16, 1995, by Imrich et al; WO 94/29696, published Dec. 22,1994, by Miller et al.; and WO 94/01775, published Jan. 20, 1994, byPawlak et al.; all of which are incorporated by reference herein. Alateral flow assay is an example of a single-step assay. In asingle-step assay, once the sample has been obtained and made ready fortesting, only a single action is necessary on the part of the user todetect the present of an analyte. For example, the sample, in whole orpart, can be applied to a device that measures analyte in the sample. Inone embodiment, a sample is placed in a lateral flow apparatus thatincludes the following components: (a) a support structure defining aflow path; (b) a labeling reagent comprising a bead conjugated to aspecific antibody, the labeling reagent being impregnated within thesupport structure in a labeling zone; and (c) a capture reagent. Thecapture reagent is located downstream of the labeling reagent within acapture zone fluidly connected to the labeling zone in such a mannerthat the labeling reagent can flow from the labeling zone into thecapture zone. The support structure comprises a material that does notimpede the flow of the beads from the labeling zone to the capture zone.Suitable materials for use as a support structure include ionic (i.e.,anionic or cationic) material. Examples of such a material include, butare not limited to, nitrocellulose, PVDF, or carboxymethylcellulose. Thesupport structure defines a flow path that is lateral and is dividedinto zones, namely a labeling zone and a capture zone. The apparatus canfurther include a sample receiving zone located along the flow path,preferably upstream of the labeling reagent. The flow path in thesupport structure is created by contacting a portion of the supportstructure downstream of the capture zone, preferably at the end of theflow path, to an absorbent capable of absorbing excess liquid from thelabeling and capture zones.

In another embodiment, a lateral flow apparatus used to detect abiomarker includes: (a) a support structure defining a flow path; (b) alabeling reagent comprising an anti-biomarker antibody as describedabove, the labeling reagent impregnated within the support structure ina labeling zone; and (c) a capture reagent, the capture reagent beinglocated downstream of the labeling reagent within a capture zone fluidlyconnected to the labeling zone in such a manner that the labelingreagent can flow from the labeling zone into the capture zone. Theapparatus preferably also includes a sample receiving zone located alongthe flow path, preferably upstream of the labeling reagent. Theapparatus preferably also includes an absorbent located at the end ofthe flow path. One preferred embodiment includes a capture reagentcomprising a biomarker binding compound.

One embodiment of the present invention is a “dipstick” device that candetect biomarkers in individuals. Dipsticks may be constructed in avariety of ways that partly depend on the way in which they will beused. They may be held directly in a sample (e.g., a urine stream),dipped directly in sample contained in a collection vessel, or havesample applied to a strip contained in a plastic cassette or platform.Another example of a dipstick is a “flow-through” device, an example ofwhich is a heterogenous immunometric assay system based on a captureantibody immobilized onto a membrane attached to an absorbent reservoir,A “bead” refers to a particulate substrate composed of a matrix such aslatex or polystyrene, which can be covalently or non-covalentlycross-linked to a detection molecule. A preferred embodiment of the“dipstick” assay is an immunometric system, described in U.S. Pat. No.5,656,502, issued on Aug. 12, 1997, to MacKay and Fredrickson, and U.S.Pat. No. 6,001,658, issued Dec. 14, 1999 to Fredrickson, bothincorporated herein by reference. Particularly preferred is anIMMUNODIP™ device available from Diagnostic Chemicals Ltd., PEI, Calif.

In addition to the immunological methods described above, variousmethods of detecting and/or determining the level of a biomarkerinclude, but are not limited to, refractive index spectroscopy (RI),ultra-violet spectroscopy (UV), fluorescence analysis, electrochemicalanalysis, radiochemical analysis, near-infrared spectroscopy (near-IR),infrared (IR) spectroscopy, nuclear magnetic resonance spectroscopy(NMR), light scattering analysis (LS), mass spectrometry, pyrolysis massspectrometry, nephelometry, dispersive Raman spectroscopy, gaschromatography, liquid chromatography, gas chromatography combined withmass spectrometry, liquid chromatography combined with massspectrometry, matrix-assisted laser desorption ionization-time of flight(MALDI-TOF) combined with mass spectrometry, ion spray spectroscopycombined with mass spectrometry, capillary electrophoresis, colorimetryand surface plasmon resonance (such as according to systems provided byBiacore Life Sciences). See also PCT Publications WO/2004/056456 andWO/2004/088309. In this regard, biomarkers can be measured using theabove-mentioned detection methods, or other methods known to the skilledartisan. Other biomarkers can be similarly detected using reagents thatare specifically designed or tailored to detect them.

Once the level of a biomarker has been determined, the level may becompared to the normal level of the same biomarker and a determinationof whether or not the individual has cancer can be made. As previouslydescribed, elevated levels of one or more of the biomarkers disclosedherein indicate the individual has cancer. In one embodiment, anelevated level of at least two compounds selected from the groupconsisting of creatine riboside, metabolite 561+, cortisol sulfate andN-acetylneuraminic acid in a sample obtained from the individual,indicates the presence of cancer. Comparison of the level of biomarkerin the individual being tested to the normal level may be performed byany method that allows the detection of the level of a biomarker. Forexample, if immunoassays (e.g., ELISA) are used to determine levels of abiomarker, a corresponding immunoassay may be performed using a samplefrom a normal individual and the numeric results from the assayscompared. Assay of the normal sample may be performed at the same timeas the test sample or it may be performed prior to, or after, the levelof biomarker in the test sample is determined. Biomarkers levels fromthe individual being tested can also be compared to a historical normalvalue, which is a value obtained from one or more cancer-freeindividuals over time. Comparison of the results may be performedvisually or they may be performed by a machine (e.g., computer).Further, if the results are performed by machine, the output of suchcomparison may be a numeric value, such as the difference betweenvalues, or it may be a qualitative result, such as a yes or no withregard to the presence of cancer. Similar methods of comparison may beperformed using any of the detection methods disclosed herein (e.g.,mass spectrometry).

In certain embodiments, the number of biomarkers chosen for measurement,and the sample used to determine the level of the biomarker will vary.For example, in some instances, determination of the level of a singlebiomarker is sufficient for the detection of cancer. Examples of useful,single biomarkers include, but are not limited to, creatine riboside andN-acetylneuraminic acid (NANA). Thus, one embodiment of the presentinvention is a method to detect the presence of cancer in an individual,the method comprising determining the level of one or more biomarkersselected from the group consisting of creatine riboside and NANA in asample from the individual, wherein elevated levels of creatine ribosideor NANA indicates the presence of cancer in the individual. In oneembodiment, the biomarker being measured is creatine riboside. In oneembodiment, the biomarker being measured is NANA. In one embodiment, thelevel of biomarker is determined from a tissue sample. In oneembodiment, the level of biomarker is determined from at least one bodyfluid selected from the group consisting of plasma, serum and urine. Inone embodiment, the body fluid is urine. In one embodiment the cancer iscolon cancer. In one embodiment, the cancer is lung cancer. In oneembodiment, the cancer is adenocarcinoma.

In other embodiments, the choice of biomarker, and the number ofbiomarkers measured, may depend on the type of cancer for which theindividual is being screened. For example, the inventors havedemonstrated that elevated levels of cortisol sulfate in some bodyfluids are indicative of the presence of lung cancer. Thus, oneembodiment of the present invention is a method to detect the presenceof lung cancer in an individual, the method comprising determining thelevel of cortisol sulfate in body fluid obtained from the individual,wherein elevated levels of cortisol sulfate indicates the presence ofcancer in the individual. In one embodiment, the body fluid may beplasma, serum or urine. In one embodiment, the cancer is adenocarcinoma.In one embodiment, the cancer is squamous cell carcinoma.

In certain embodiments, elevated levels of a specific biomarker in aparticular bodily fluid are indicative of the presence of specific typesof cancers. For example, the inventors have discovered that elevatedlevels of N-acetylneuraminic acid in the urine are indicative of lungcancer. Thus, one embodiment of the present invention is a method todetect the presence of cancer in an individual, the method comprisingdetermining the level of N-acetylneuraminic acid in urine from theindividual, wherein elevated levels of urinary N-acetylneuraminic acidindicates the presence of lung cancer in the individual. In oneembodiment the cancer is an adenocarcinoma. In one embodiment, thecancer is squamous cell carcinoma.

Because the levels of biomarkers of the present invention may be used todetect cancer, they may therefore be used to identify individuals havingcancer. Thus, one embodiment of the present invention is a method foridentifying an individual having cancer, the method comprisingdetermining the level of at least two biomarkers in a body fluidobtained from an individual, wherein the at least two biomarkers areselected from the group consisting of creatine riboside, metabolite561+, cortisol sulfate and N-acetylneuraminic acid, and wherein elevatedlevels of the at least two biomarkers identifies the individual ashaving cancer. One embodiment of the present invention is a method foridentifying an individual having cancer, the method comprisingdetermining the level of at least three biomarkers in a body fluidobtained from an individual, wherein the at least three biomarkers areselected from the group consisting of creatine riboside, metabolite561+, cortisol sulfate and N-acetylneuraminic acid, and wherein elevatedlevels of the at least three biomarkers identifies the individual ashaving cancer. One embodiment is a method for identifying an individualhaving cancer, comprising determining the level of creatine riboside,metabolite 561+, cortisol sulfate and N-acetylneuraminic acid, whereinelevated levels creatine riboside, metabolite 561+, cortisol sulfate andN-acetylneuraminic acid identify the individual as having cancer. Oneembodiment of the present invention is a method to identify anindividual having cancer, the method comprising determining the level ofone or more biomarkers selected from the group consisting of creatineriboside and NANA, wherein elevated levels of creatine riboside and/orNANA identifies the individual as having cancer. In one embodiment thecancer is colon cancer. In one embodiment the cancer is lung cancer. Inone embodiment the cancer is adenocarcinoma. In one embodiment thecancer is squamous cell carcinoma.

One embodiment of the present invention is a method to identify anindividual having lung cancer, the method comprising determining thelevel of cortisol sulfate in a body fluid obtained from an individual,wherein elevated levels of cortisol sulfate identify the individual ashaving lung cancer. One embodiment of the present invention is a methodto identify an individual having lung cancer, the method comprisingdetermining the level of N-acetylneuraminic acid in urine obtained froman individual, wherein elevated levels of urinary N-acetylneuraminicacid identifies the individual as having lung cancer.

If an individual has been identified as having cancer, that individualmay also be identified as being in need of treatment for cancer. As usedherein, a treatment or therapy for cancer refers to any treatment ortherapy that is intended to reduce the cancer load or prevent the cancerload from increasing. Examples of treatments include, but are notlimited to, surgery, chemotherapy, biotherapy and radiation. Accordingto the present invention, the term cancer load may refer to the mass,size or number of cancer cells present in a patient. Thus, for example,if the pre-treatment and post-treatment biomarker levels remainsubstantially unchanged, this would indicate that the treatment ispreventing an increase in cancer load. If the difference between thepre-treatment and post-treatment biomarker levels decrease, this is anindication that the treatment is reducing the cancer load. In oneembodiment, the at least two biomarkers are selected from the groupconsisting of creatine riboside, metabolite 561+, cortisol sulfate andN-acetylneuraminic acid. In one embodiment, the level of at least threebiomarkers are determined, wherein the biomarkers are selected from thegroup consisting of creatine riboside, metabolite 561+, cortisol sulfateand N-acetylneuraminic acid. In one embodiment, the level of creatineriboside, metabolite 561+, cortisol sulfate and N-acetylneuraminic acidare detected.

Methods disclosed herein may be used to monitor the efficacy of a cancertreatment. For example, in patients undergoing treatment for cancer, itis desirable for tumor size to be diminished and, eventually, for thepatient to be free of cancer. Consequently, the levels of tumor-specificbiomarkers should also return to normal. Thus, one embodiment of thepresent invention is a method for monitoring the efficacy of a cancertreatment, the method comprising:

a) determining the level of one or more biomarkers of the presentinvention in a patient having cancer to obtain a pre-treatment level ofthe one or more biomarkers;

b) administering a cancer treatment to the patient;

c) at a period of time following administration of the treatment,determining the level of the one or more biomarkers of the presentinvention in the patient to obtain a post-treatment level of the one ormore biomarkers; and

d) comparing the pre-treatment and post-treatment biomarker levels todetermine the efficacy of the treatment. In one embodiment, efficacy oftreatment for cancer is monitored by determining the level of one ormore biomarkers selected from the group consisting of creatine ribosideand N-acetylneuraminic acid (NANA). In one embodiment, efficacy oftreatment for cancer is monitored by determining the level of at leasttwo biomarkers selected from the group consisting of creatine riboside,metabolite 561+, cortisol sulfate and N-acetylneuraminic acid in bodyfluid obtained from the individual. In one embodiment, efficacy oftreatment for lung cancer is monitored by determining the level ofcortisol sulfate in a sample of body fluid from the individual. In oneembodiment, efficacy of treatment for lung cancer is monitored bydetermining the level of N-acetylneuraminic acid in urine from theindividual.

The inventors have also discovered that the levels of certain biomarkersof the present invention are useful for predicting the prognosis of apatient having cancer. In particular, the inventors have discovered thatthe levels of creatine riboside and metabolite 561+ are related to theprognosis of a patient having cancer. Thus, one embodiment of thepresent invention is a method for predicting the prognosis of anindividual having cancer, the method comprising determining the level ofat least one biomarker selected from the group consisting of creatineriboside and metabolite 561+, wherein an elevated level of the at leastone biomarker is indicative of the prognosis of the individual. In oneembodiment, the levels of creatine riboside and metabolite 561+ aredetermined. In a particular embodiment, the at least one biomarker levelis determined when the cancer is in an early stage. In one embodiment,an elevated level of the at least one biomarker indicates a reducedsurvival time relative to a cancer patient in whom the level of the atleast one biomarker is not elevated. In one embodiment, elevated levelsof creatine riboside and metabolite 561+ indicate a reduced survivaltime relative to a cancer patient in whom the levels of creatineriboside and metabolite 561+ are not elevated.

It should be appreciated that the diagnostic and prognostic accuracy ofbiomarkers of the present invention may be improved when the levels ofsuch biomarkers are measured in combination with the level or presenceof other, known cancer biomarkers. The known biomarker may be anymolecule for which an association between the level or presence of themolecule and a diagnosis of cancer (or a prognosis related thereto) hasbeen established. Examples of known biomarkers to measure include, butare not limited to, proteins, nucleic acid molecules, lipids,carbohydrates and combinations thereof. One type of known biomarker tomeasure in combination with one or more biomarker of the presentinvention is a microRNA (miRNA). MicroRNAs are small, non-coding RNAs,that have been shown to regulate epigenetic phenomena (Lee, R C,Feinbaum R L, Ambros, V. The C. elegans heterochronic gene lin-4 encodessmall RNAs with antisense complimentarity to lin-14. Cell 993;75(5):843-54). These small RNA molecules, which are usually 18-25nucleotides in size, repress the translation of target genes bycomplimentary binding to their 3′UTR sequence (Carthew, R W, SontheimerE J. Origins and Mechanisms of miRNAs and siRNAs. Cell 2009;136(4):642-55). Since their discovery, miR-mediated post-transcriptionalmodulation of gene expression has been found to be associated with anumber of diseases, including cancer (Yang B, Lin H, Xiao J, et al. Themuscle-specific microRNA miR-1 regulates cardiac arrhythmogenicpotential by targeting GJA1 and KCNJ2. Nat Med 2007; 13(4):486-91; SaitoM, Schetter A J, Mollerup S, et al. The association of microRNAexpression with prognosis and progression in early-stage, non-small celllung adenocarcinoma: a retrospective analysis of three cohorts. ClinCancer Res 2011; 17(7):1875-82; Park J K, Lee E J, Esau C, et al.Antisense inhibition of microRNA-21 or -221 arrests cell cycle, inducesapoptosis, and sensitizes the effects of gemcitabine in pancreaticadenocarcinoma. Pancreas 2009; 38(7):e190-9; Markou A, Tsaroucha E G,Kaklamanis L, et al. Prognostic value of mature microRNA-21 andmicroRNA-205 overexpression in non-small cell lung cancer byquantitative real-time R T-PCR. Clin Chem 2008; 54(10):1696-704; Esau C,Davis S, Murray S F, et al. miR-122 regulation of lipid metabolismrevealed by in vivo antisense targeting. Cell Metab 2006; 3(2):87-98;Bakirtzi K, Hatziapostolou M, Karagiannides I, et al. Neurotensinsignaling activates microRNAs-21 and -155 and Akt, promotes tumor growthin mice, and is increased in human colon tumors. Gastroenterology 2011;141(5):1749-61 el; Asangani I A, Rasheed S A, Nikolova D A, et al.MicroRNA-21 (miR-21) post-transcriptionally downregulates tumorsuppressor Pdcd4 and stimulates invasion, intravasation and metastasisin colorectal cancer. Oncogene 2008; 27(15):2128-36) In fact, a numberof miRs have been found to be deregulated in several types of cancers(Park J K, Lee E J, Esau C, et al. Antisense inhibition of microRNA-21or -221 arrests cell cycle, induces apoptosis, and sensitizes theeffects of gemcitabine in pancreatic adenocarcinoma. Pancreas 2009;38(7):e190-9; Bakirtzi K, Hatziapostolou M, Karagiannides I, et al.Neurotensin signaling activates microRNAs-21 and -155 and Akt, promotestumor growth in mice, and is increased in human colon tumors.Gastroenterology 2011; 141(5):1749-61 el; Asangani I A, Rasheed S A,Nikolova D A, et al. MicroRNA-21 (miR-21) post-transcriptionallydownregulates tumor suppressor Pdcd4 and stimulates invasion,intravasation and metastasis in colorectal cancer. Oncogene 2008;27(15):2128-36; Papagiannakopoulos T, Shapiro A, Kosik K S. MicroRNA-21targets a network of key tumor-suppressive pathways in glioblastomacells. Cancer Res 2008; 68(19):8164-72; Meng F, Henson R, Wehbe-Janek H,et al. MicroRNA-21 regulates expression of the PTEN tumor suppressorgene in human hepatocellular cancer. Gastroenterology 2007;133(2):647-58; Volinia S, Calin G A, Liu C G, et al. A microRNAexpression signature of human solid tumors defines cancer gene targets.Proc Natl Acad Sci USA 2006; 103(7):2257-61; Takahashi Y, Forrest A R,Maeno E, et al. MiR-107 and MiR-185 can induce cell cycle arrest inhuman non small cell lung cancer cell lines. PLoS One 2009; 4(8):e6677).For example, mir-21 has been found to be up-regulated in most cancersites, including lung, pancreas, liver and colon (Saito M, Schetter A J,Mollerup S, et al. The association of microRNA expression with prognosisand progression in early-stage, non-small cell lung adenocarcinoma: aretrospective analysis of three cohorts. Clin Cancer Res 2011;17(7):1875-82; Park J K, Lee E J, Esau C, et al. Antisense inhibition ofmicroRNA-21 or -221 arrests cell cycle, induces apoptosis, andsensitizes the effects of gemcitabine in pancreatic adenocarcinoma.Pancreas 2009; 38(7):e190-9; Markou A, Tsaroucha E G, Kaklamanis L, etal. Prognostic value of mature microRNA-21 and microRNA-205overexpression in non-small cell lung cancer by quantitative real-time RT-PCR. Clin Chem 2008; 54(10):1696-704; Asangani I A, Rasheed S A,Nikolova D A, et al. MicroRNA-21 (miR-21) post-transcriptionallydownregulates tumor suppressor Pdcd4 and stimulates invasion,intravasation and metastasis in colorectal cancer. Oncogene 2008;27(15):2128-36; Meng F, Henson R, Wehbe-Janek H, et al. MicroRNA-21regulates expression of the PTEN tumor suppressor gene in humanhepatocellular cancer. Gastroenterology 2007; 133(2):647-58). Anincrease in miR-21 expression has been associated with poor prognosis inlung cancer patients (Saito M, Schetter A J, Mollerup S, et al. Theassociation of microRNA expression with prognosis and progression inearly-stage, non-small cell lung adenocarcinoma: a retrospectiveanalysis of three cohorts. Clin Cancer Res 2011; 17(7):1875-82; MarkouA, Tsaroucha E G, Kaklamanis L, et al. Prognostic value of maturemicroRNA-21 and microRNA-205 overexpression in non-small cell lungcancer by quantitative real-time R T-PCR. Clin Chem 2008;54(10):1696-704; Akagi I, Okayama H, Schetter A J, et al. Combination ofProtein Coding and Noncoding Gene Expression as a Robust PrognosticClassifier in Stage I Lung Adenocarcinoma. Cancer Res 2013), and isbelieved to promote tumor invasiveness and metastasis (Asangani I A,Rasheed S A, Nikolova D A, et al. MicroRNA-21 (miR-21)post-transcriptionally downregulates tumor suppressor Pdcd4 andstimulates invasion, intravasation and metastasis in colorectal cancer.Oncogene 2008; 27(15):2128-36; Okayama H, Saito M, Oue N, et al. NOS2enhances KRAS-induced lung carcinogenesis, inflammation and microRNA-21expression. Int J Cancer 2013; 132(1):9-18; Wang Z X, Bian H B, Wang JR, et al. Prognostic significance of serum miRNA-21 expression in humannon-small cell lung cancer. J Surg Oncol 2011; 104(7):847-51). Moreover,inhibition of miR-21 expression has been found to reverse suchphenotypes in model systems (Yang B, Lin H, Xiao J, et al. Themuscle-specific microRNA miR-1 regulates cardiac arrhythmogenicpotential by targeting GJA1 and KCNJ2. Nat Med 2007; 13(4):486-91; RenJ, Zhu D, Liu M, et al. Downregulation of miR-21 modulates Rasexpression to promote apoptosis and suppress invasion of Laryngealsquamous cell carcinoma. Eur J Cancer 2010; 46(18):3409-16).

Thus, in one embodiment the presence of cancer is detected by measuringthe level of one or more biomarkers in conjunction with the level of oneor more microRNAs. Methods of measuring miRNA levels are known to thoseskilled in the art. According to the present invention, the level ofmiRNA may or may not be determined at the same time as the level of theone or more biomarker of the present invention. Similarly, the level ofmiRNA may or may not be determined using the sample from which the levelof the one or more biomarker is determined. In one embodiment, thecancer is lung cancer. In one embodiment, the cancer is adenocarcinomaor squamous cell carcinoma. In one embodiment, the one or more biomarkeris selected from the group consisting of creatine riboside, metabolite561+, cortisol sulfate and N-acetylneuraminic acid.

Also included in the present invention are kits useful for practicingthe disclosed methods of the present invention. Thus, one embodiment ofthe present invention is a kit for identifying an individual havingcancer, in accordance with the present invention, the kit comprising i)reagents for selectively detecting the presence, absence or level of, atleast one or more biomarkers in a sample obtained from the subject andii) instructions for using the kit. One embodiment of the presentinvention is a kit for detecting cancer or identifying an individualhaving cancer, in accordance with the present invention, the kitcomprising i) reagents for selectively detecting the presence, absenceor level of, at least one biomarker of the present invention in a sampleobtained from the subject and ii) instructions for using the kit.

Kits of the present invention will contain at least some of the reagentsrequired to determine the presence, absence or level of biomarkers ofthe present invention. Reagents for kits of the present invention caninclude, but are not limited to, isolated biomarkers of the presentinvention, and compounds that bind biomarkers of the present invention(e.g., an antibody that selectively binds to a biomarker of the presentinvention). In some embodiments, the biomarker protein and/or thebiomarker-binding compound may be fixed to a solid substrate. The kitsmay further comprise control proteins. One skilled in the art will,without undue experiments, be able to select the necessary reagents fromthe disclosure herein, in accordance with the usual requirements.Reagents of the kit may also comprise a molecular label or tag.

Kits of the present invention can also comprise various reagents, suchas buffers, necessary to practice the methods of the invention, as knownin the art. These reagents or buffers may, for example, be useful toextract and/or purify biomarkers from the biological sample obtainedfrom the subject. The kit may also comprise all the necessary materialsuch as microcentrifuge tubes necessary to practice the methods of theinvention.

EXAMPLES Example 1

This Example demonstrates the methodology used to identify biomarkers ofthe present invention.

Urine samples from 469 lung cancer patients prior to treatment and 536population controls collected from 1998 to 2007 from the greaterBaltimore, Md. area were used as a training set. Patients were recruitedfrom pathology departments in seven hospitals: Baltimore VeteransAdministration Medical Center, Bon Secours Hospital, Harbor HospitalCenter, Sinai Hospital, Johns Hopkins Bayview Medical Center, The JohnsHopkins Hospital, and University of Maryland Medical Center. Populationcontrols were identified from the Department of Motor Vehicles lists andfrequency-matched to cases by age, gender, and ethnicity (Zheng Y L,Loffredo C A, Yu Z, et al. Bleomycin-induced chromosome breaks as a riskmarker for lung cancer: a case-control study with population andhospital controls. Carcinogenesis 2003; 24:269-74; Olivo-Marston S E,Yang P, Mechanic L E, et al. Childhood exposure to secondhand smoke andfunctional mannose binding lectin polymorphisms are associated withincreased lung cancer risk. Cancer Epidemiol Biomarkers Prev 2009;18:3375-83; Zheng Y L, Kosti O, Loffredo C A, et al. Elevated lungcancer risk is associated with deficiencies in cell cycle checkpoints:genotype and phenotype analyses from a case-control study. Int J Cancer2010; 126:2199-210). An additional set of 80 recently diagnosed casesand 78 population controls were used as a validation set. Forty-eightcancerous and non-cancerous stage I tissue pairs, of which 20 are asubset of the training set, were also utilized. Survival times werecalculated as time of diagnosis to time of death or to follow-up (2010);death due to cancer was determined from the NDI extraction of the deathcertificates. This study is approved by the Institutional Review Boardsof the seven institutions. Urine biospecimens were collected prior tothe administration of chemotherapy. The patient characteristics for eachsample set are shown below in Table 1.

TABLE 1 Sample characteristics. Trainining Set Validation Set ^(†)Tissue Set Population Population Tumor/Adjacent All Cases Controls AllCases Controls Normal Pairs (N = 1005) (N = 469) (N = 536) (N = 158) (N= 80) (N = 78) (N = 48) Age (mean = 66.4) (mean = 66.2) (mean = 66.6)(mean = 66.7) (mean = 64.2) (mean = 68.7) (mean = 68.9) >mean 519 240279 82 35 47 27 <=mean 486 229 257 76 45 31 21 Smoking Status Ever 10Current 293 222 71 46 38 8 17 Former 463 214 249 73 31 42 17 Never 24933 216 39 11 28 4 Histology ADC 216 51 31 SCC 122 14 16 NSCLC 131 10 1Gender Female 492 232 260 81 46 35 24 Male 513 237 276 77 34 43 24 RaceAfrican 366 127 239 70 35 35 9 American Caucasian 639 342 297 88 45 4339 Stage* I-II 213 31 48 III-IV 103 41 0 *Only pathologically stagedcases, according to the 7th edition of the Cancer Staging Manual of theAmerican Joint Committee on Cancer, were utilized for stratifiedanalyses. ^(†) Five samples are missing histology, and eight samples aremissing stage information.

Detailed clinical information derived from extensive questionnaires wasavailable for each patient, including age, gender, race, smoking status(never smokers, having smoked less than 100 cigarettes in theirlifetime; former smokers, having quit smoking at least 6 months prior tothe interview date), pack years, histology, AJCC staging, and survival.Lung cancer diagnosis was pathologically determined. Staging wasperformed by a pathologist using the seventh edition of the CancerStaging Manual of the American Joint Committee on Cancer (AJCC) (Edge S,Byrd D R, Compton C C, Fritz A G, Greene F L, Trotti A, ed. AJCC CancerStaging Manual. 7th ed: Springer-Verlag; 2010).

Urine samples were analyzed using a quadrupole time-of-flight (QTOF)mass spectrometer (Premier, Waters), in positive (ESI+) and negative(ESI−) electrospray ionization modes, using a 50×2.1 mm Acquity 1.7 μmC18 column (Waters Corp, Millford, Mass.). Briefly, urine samples werediluted with an equal volume of 50% aqueous acetonitrile containingdebrisoquine (ESI+ internal standard) and 4-nitrobenzoic acid (ESI−internal standard). Samples were centrifuged at 14,000×g for 20 minutesat 4° C. to precipitate proteins. Five μl was chromatographed on a50×2.1 mm Acquity BEH 1.7 μm C18 column (Waters) using an Acquity UPLCsystem (Waters). To avoid artifacts based on sample injection order, theorder was randomized. The gradient mobile phase consisted of 0.1% formicacid (A) and acetonitrile containing 0.1% formic acid (B). A typical10-min sample run (at 0.5 ml/min) consisted of 0.5 min of 100% solvent Afollowed by a linear gradient to 80% A at 4 min, to 5% A at 8 min. Aftera 0.5 min wash step, the column was equilibrated to initial conditionsfor 1.5 min. The eluent was introduced by electrospray ionization intothe QTOF mass spectrometer (Premier, Waters) operating in positive(ESI+) or negative (ESI−) ionization mode. The capillary and samplingcone voltages were set to 3,000 and 30 V, respectively. Source anddesolvation temperatures were set to 120° C. and 350° C., respectively,and the cone and desolvation gas flows were set to 50.0 and 650.0 L/h,respectively. To maintain mass accuracy, sulfadimethoxine at aconcentration of 300 pg/μl in 50% aqueous acetonitrile was used as alock mass and injected at a rate of 50 μl/min. For MS scanning, datawere acquired in centroid mode from 50 to 850 m/z and for tandem MS thecollision energy was ramped from 5 to 35 V. Four different qualitycontrol sets were included with the runs to assess machine sensitivityand sample carry over. First, 169 “pooled” samples, containing aliquotsfrom 108 urine samples, were processed randomly throughout the run.Second, a standard cocktail containing theophylline, caffeine, hippuricacid, 4-nitrobenzoic acid, and nortriptyline (designated as MetMix) wasinjected every 100 samples. Third, 32 blanks were randomly injected toassess sample carry over. Fourth, 48 samples with 4 high purity nicotinemetabolite standards, including cotinine, nicotine-N′-oxide, anabasine,and trans-3′-hydroxycotinine (Sigma-Aldrich), were spiked into urine.Fifth, 10% of the samples were randomly selected and processed induplicate at the end of the run to evaluate chromatogram consistency.Finally, debrisoquine and 4-nitrobenzoic acid were spiked into samplesfor runs in ESI+ and ESI− modes, respectively.

Chromatograms from the training set (N=1005) were visually inspectedusing Mass Lynx (Waters), and peaks were extracted, retention timesaligned, and peak areas quantitated using the freely available R packageXCMS⁴⁸. ESI+ and ESI− peak areas were normalized using the MSTUS method(Warrack B, Hnatyshyn S, Ott K H, Zhang H, Sanders M. Proceedings of the54th ASMS Conference on Mass Spectrometry and Allied Topics. In:Conference on Mass Spectrometry and Allied Topics 2006; Seattle, Wash.;2006). Chromatograms from the quantitation (N=198), validation (N=158)and the tissue sets (N=48) were processed using MarkerLynx (peak areasof the training and validation sets were normalized to total ion count[TIC]). In the training set, chromatograms were first visually inspectedusing MassLynx (Waters Corp., Milford, Mass.) to ensure their qualityand 12 samples were removed due to poor quality (e.g. undetectablespiked in control, break in signal). All subsequent data analyses wereperformed using R, a freely available language and environment forstatistical computing and graphics (Breiman L. Random Forests. MachineLearning 2001; 45:5-32; Ho T K. Random Decision Forest. Proceedings ofthe 3rd International Conference). The R package XCMS (Smith C A, Want EJ, O'Maille G, et al. XCMS: processing mass spectrometry data formetabolite profiling using nonlinear peak alignment, matching, andidentification. Anal Chem 2006; 78(3):779-87.), version 1.22.1, wasutilized to extract and align peaks for all detected metabolites. Peakareas for all signals were extracted using the following criteria:ppm=25, mzdiff=−0.005, snthresh=10, scanrange=c(1,500),peakwidth=c(5,12), prefilter=c(1,30)). Retention times were aligned withone iteration of the rector( ) function using the loess method, whichperforms smoothing of the retention time deviations for every time pointin each sample. Peaks were then found using the group( ) function withthe following parameters: bw=10, minfrac=0.1, mzwid=0.01. Next, ESI+ andESI− signals were merged in lung cancer cases and healthy controlsamples that were in common between both sets (N=1257) and signals withmasses that had a ppm error larger than 50 were removed from furtheranalysis. This filtering reduced the total number of signals from 2756and 1804 to 1807 and 1359, for ESI+ and ESI− modes, respectively. Next,a normalization algorithm analogous to MSTUS (MS ‘total useful signal’)(Warrack B, Hnatyshyn S, Ott K H, Zhang H, Sanders M. Proceedings of the54th ASMS Conference on Mass Spectrometry and Allied Topics. In:Conference on Mass Spectrometry and Allied Topics Seattle, Wash., 2006)was applied. Signals that are putative xenobiotics (e.g., acetaminophen)were removed before calculating the scaling factor using the followingcriteria: signals with very high abundance (>90th percentile) in at most100 samples and with very low abundance (<=20th percentile) in at least800 samples. Scaling factors, total intensity counts for each sampledivided by the mean total intensity counts of all samples, were thenused to normalize signal abundances. Finally, signals with variation(measured by coefficients of variation) between duplicates higher thanvariations between randomly selected sample pairs were removed.

The validation set data from 158 samples was also processed using XCMS Rpackage following the same parameters outlined for the original set.

The quantitation (N=198) and the tissue sets (N=96) were processed usingTargetLynx software (Waters), by extracting only the four ions ofinterest and using the following parameters: chromatogram mass window of20 ppm; retention time windows of 0.35 min (creatine riboside), 0.15(561+), 0.2 (cortisol sulfate), 0.1 (N-acetylneuraminic acid); smoothingenabled; smoothing method (1); smoothing iterations (1); smoothing width(1); apex track enabled; peak to peak baseline noise automaticallycalculated; peak width @ 5% height (0.130); baseline start and end(0.00, 0.50); detection of shoulder peaks disabled; thresholdparameters: relative and absolute height disabled, threshold relativearea (10), threshold absolute area disabled; integration window extent(1); propagation of integration parameters disabled.

Identification of putative biomarkers was initiated by searching theirhigh accuracy masses in METLIN and HMDB databases (Wishart D S, Tzur D,Knox C, et al. HMDB: the Human Metabolome Database. Nucleic Acids Res2007; 35:D521-6; Smith C A, O'Maille G, Want E J, et al. METLIN: ametabolite mass spectral database. Ther Drug Monit 2005; 27:747-51). Ifno database hits were returned, spectral interpretation of the MS/MSproduct ion mass and MS3 spectra were used to generate putativestructures. Metabolite identity was confirmed using commerciallyavailable and in-house synthesized standards, by comparison of retentiontime, product ion mass spectra and by monitoring characteristicfragmentation patterns in multiple reaction monitoring (MRM) mode. Thestructure of the novel metabolite, creatine riboside, was also confirmedby NMR. See FIG. 5 for m/z (mass to charge ratio), retention time andMRM specifics regarding the four molecules/biomarkers described in thisinvention.

Unsupervised clustering revealed a clear separation between urine andquality control samples, a global indication of successful measurements(FIG. 2A). To further check measurement reproducibility within a run,169 (˜15%) duplicate samples were processed randomly and showed a verystrong correlation, with Spearman's r>0.85 for most samples (FIG. 2B).Furthermore, the distribution of coefficients of variation (CVs) isexpectedly smaller (P<0.00001) for the quality control compared to thestudy subject samples (FIG. 2C). Finally, a global increase in cotinine,nicotine-N′-oxide, and trans-3′-hydroxycotinine was observed in currentcompared to former and non-smokers, thereby confirming the ability todetect these key metabolites (FIG. 3).

The identities of the molecules described in this invention wereconfirmed as follows:

The identity of N-acetylneuraminic acid (formula=C11H19NO9) wasconfirmed using a commercially available standard (Sigma-Aldrich,CAS#131-48-6).

The identity of cortisol sulfate (formula=C21H30O8S) was confirmed bysynthesizing cortisol-21-sulfate (CAS#1253-43-6) in house. All chemicalswere purchased from Sigma-Aldrich. Cortisol-21-sulfate was prepared fromcortisol using modification of reported method for sulfation usingchlorosulfonic acid [Lloyd A G. Fractionation of the products of thedirect sulphation of monosaccharides on anion-exchange resin. Biochem J1962; 83:455-60.]. Briefly, 0.5 gm cortisol was added to 2.5 ml drypyridine in a round bottom flask, chilled on ice and 0.2 mlchlorosulfonic acid was added dropwise with swirling. The reactionmixture was swirled for 45 min on ice followed by the addition of 1 mldistilled water. Solvent was removed on rotary evaporator, residuere-dissolved in 20 ml water, neutralized by addition of NaHCO3.Cortisol-21-sulfatewas purified from the reaction mixture using anionexchange resin as described earlier [ref Mumma R O, Hoiberg C P, Weber WW, 2nd. Preparation of sulfate esters. The synthesis of steroid sulfatesby a dicyclohexylcarbodimide-mediated sulfation. Steroids 1969;14(1):67-74.]. Purity of the compound was found to be >95% by NMR.

Creatine riboside (formula=C9H17N3O6) is a novel compound describedherein, and synthesized in house. Synthesis of creatine riboside isbased on the Maillard reaction (Hodge J E. Dehydrated foods: chemistryof browning reactions in model systems. J Agr Food Chem 1953; 1:928-43)and the knowledge that ribose is considerably more reactive than glucose[ref. Bunn H F, Higgins P J. Reaction of monosaccharides with proteins:possible evolutionary significance. Science 1981; 213(4504):222-4). In atest tube, 20 mg ammonium bicarbonate, 60 mg D-(−)-ribose, and 6 mgcreatine monohydrate were combined, mixed by vortexing, and heated at80° C. for 10 min in a shaking heating block. The synthesis product wasstored at −20° C. until analysis.

The structure of creatine riboside was determined using UPLC-QTOF MS/MS.The reaction product was separated on a Acquity BEH Amide 1.7 μm 2.1×50mm column (Waters) which was maintained at 40° C. throughout the rununder HILIC conditions using a mixture of (A) 10 mM ammonium acetate in90% acetonitrile (pH=8.9) and (B) 10 mM ammonium acetate in 10%acetonitrile (pH=8.9) as mobile phase. The gradient elution wasperformed over 10 min using: 1-60% B in 4 min (0.4 ml/min), 60-80% B at8 min (0.4 ml/min), holding at 80% B up to 8.5 min (0.3 ml/min),bringing back to 1% B at 8.8 min and holding at 1% until end (0.3ml/min). The column was re-equilibrated with 99% A at the end of eachrun prior to injection of next sample. The eluent was introduced viaelectrospray into a Synapt G2S mass spectrometer (Waters) and tandem MSwas generated for 264.1196+ corresponding to the predicted m/z forcreatine riboside. Retention time and m/z were compared for thesynthesized creatine riboside and the metabolite putatively identifiedas creatine riboside in the urine samples (FIG. 5). Further spectralinterpretation was conducted using Mass Frontier v7.0 (Thermo FisherScientific, Waltham, Mass.) selecting the daughter ion m/z=90.0550+ asthe final fragment. Results are shown in FIG. 5A, which demonstratesthat the in silico predicted fragments (using the default settings)correspond with the fragments of 264.1196+ identified in the syntheticstandard and urine sample.

The synthesis of creatine riboside is further supported from the ¹H-¹3CHMBC spectrum of the reaction mixture between ribose and creatine indmso-d⁶. HMBC is a 2D NMR experiment which gives the long range (2- or3-bonds) couplings between protons and carbons. As can be seen (FIG. 6),there is a cross peak between the anomeric sugar proton of ribose at4.61 ppm and the carbon at 156.19 ppm of creatine, indicating thecovalent attachment between the two units.

Analysis of compound 561+ indicates the molecule is a glucoronidatedlipid. The MS/MS spectra for compound 561+ from urine (FIG. 5D) shows aloss of 176, characteristic for glucuronides. This observation alongwith a fact that acid hydrolysis causes a complete loss of 561+ peak inurine provide evidence that 561+ is a glucoronide. Additionally, thereis a loss of two 18 amu (H2O) as evident in the MSMS product ionspectrum, which would indicate two other —OH groups in addition to theone attached to glucuronic acid.

Example 2

This Example demonstrates the ability of methodology of the presentinvention to predict the smoking status and/or the cancer status of testindividuals.

Subjects were classified by their smoking status (smokers versusnonsmokers) and 87% of the samples were correctly classified. Theresults of this classification are shown below in Table 2.

TABLE 2 Classification of smoking status using Random forest analysis.All Signals* Top Predictive Signals** % ACC(sd)*** % ACC(sd)*** TPR/FPR**** TPR/FPR **** # Signals All Samples 86.7(0.1) 87.4(0.1) 350 (468cases and 536 65.5/3.9 68.5/4.3 controls) *Total number of signals used:31.55 **Top predictive signals: determined by maximizing % accuracies of3 iterations of random forests ***% ACC (sd) average % out of bagaccuracy and its standard deviation using 3 iterations **** TPR: truepositive rate; FPR: false positive rate

Importantly, the 3 most highly associated metabolites, ranked accordingto the importance score given by Random Forests, are cotinine,nicotine-N′-oxide, and trans-3′-hydroxycotinine, known nicotinemetabolites. This finding establishes the utility of randomforests-based classification approach to find diagnostic metabolites oflung cancer. Samples were classified as lung cancer or healthy controlsusing the R package randomForest (Breiman L. Random Forests. MachineLearning 2001; 45:5-32.; Ho T K. Random Decision Forest. Proceedings ofthe 3rd International Conference). Since there are known smoking habitdifferences between different genders and race (Kabat G C, Morabia A,Wynder E L. Comparison of smoking habits of blacks and whites in acase-control study. Am J Public Health 1991; 81:1483-6; Okuyemi K S,Ebersole-Robinson M, Nazir N, Ahluwalia J S. African-American mentholand nonmenthol smokers: differences in smoking and cessationexperiences. J Natl Med Assoc 2004; 96:1208-11), including thepreference for menthol cigarettes amongst African Americans Health 1991;81:1483-6; Okuyemi K S, Ebersole-Robinson M, Nazir N, Ahluwalia J S.African-American menthol and nonmenthol smokers: differences in smokingand cessation experiences. J Natl Med Assoc 2004; 96:1208-11; Stahre M,Okuyemi K S, Joseph A M, Fu S S. Racial/ethnic differences in mentholcigarette smoking, population quit ratios and utilization ofevidence-based tobacco cessation treatments. Addiction 2010; 105 Suppl1:75-83; Jones M R, Apelberg B J, Tellez-Plaza M, Samet J M, Navas-AcienA. Menthol Cigarettes, Race/Ethnicity and Biomarkers of Tobacco Use inUS Adults: The 1999-2010 National Health and Nutrition ExaminationSurvey (NHANES). Cancer Epidemiol Biomarkers Prev 2012), classificationsof cases and controls were initially performed on all samples, then onsamples stratified by race and gender. Proportion of samples that wereaccurately categorized as lung cancer cases or controls using optimalvariables were as follows: 78.1% using all samples, 77.7% for Caucasianmales, 78.6% for Caucasian females, 84.9% for African American males,and 82.3% for African American females. AS shown in Table 3 below, truepositive and true negative rates ranged from 77.1-84.9 and 63.2-81.7,respectively.

TABLE 3 Classification of lung cancer status using Random forestanalysis. Top Bottom All

Predictive

* Predictive

**

 ACC(

) #

put 16 ACC(

) # input 16 ACC(

) # input TPR/FPR Signals TPR/FPR Signals TPR/FPR Signals All Samples71.7 (0.5) 316

78.1 (0.5)

7

 (0.9) 30

(

 cases and 536 controls) 69.1/21.2 76.5/

64.3/

.3 Stage I Samples 71.2 (0.9) 3

7

.1 (0.7)

7 71.7 (1) 3079 (204 cases and 536 controls) 45.3/14.1 63.2/14.437.4/11.9 Caucasian Males 71.7 (2.1) 3

5 77.7 (0.6) 72

 (1.3)

(170 cases, 196 controls) 71.2/

.9

0.2/23.3

/31.6 Caucasian Females 67.7 (1.1) 31

5 78.6 (0.7) 72 61.5 (1.1)

(172 cases, 141 controls) 72.9/35.

1.7/22.3 67.2/42.2 African American Males 7

 (1.5) 31

5 84.

 (1.2) 1

2 70.1 (1.5) 3064 (67 cases, 170 controls)

/14.6 80.8/

.5 50.9/16.3 African American Females 72.

 (2.1) 3165 82.3 (1.1) 1

2 67.9 (1.5) 3014 (60 cases, 119 controls) 4

/12.1 70/10.7 36.7/14.7 *

**

indicates data missing or illegible when filed

Four metabolites contributed strongly to the classifications independentof race, gender and smoking status (See FIG. 14), and were elevated inthe urine of lung cancer patients (P<0.00001, FIG. 4A):N-acetylneuraminic acid, cortisol sulfate, creatine riboside and oneunidentified metabolite with a mass/charge ratio (m/z) of 561.3432+,confirmed to be a glucuronidated lipid compound (FIG. 5D). Creatineriboside structure was confirmed by NMR, definitively proving itsnovelty (FIG. 6).

Three metabolites (creatine riboside, N-acetylneuraminic acid, andmetabolite 561+) were confirmed to be elevated in the urine of lungcancer patients in an independent validation set (P<0.004, Table 1, FIG.4B) from the same cohort (N=158), comprising cases that were diagnosedmore recently when compared to the training sample set. Cortisolsulfate, although not significantly elevated in cases possibly due toinsufficient power, shows the expected trend. In addition, the fourmetabolites identified herein were technically validated on aquantitative Xevo TQ mass spectrometer in a subset (N=198) of thetraining set, representing similar distributions of age, gender andracial composition to the training cohort (P<0.00001, Table 1, FIG. 4C,4E). The reproducibility of metabolite measurements was confirmed by asecond quantitation carried out two years later on the same samples,resulting in intraclass correlation coefficients (ICC) from 0.82 to 0.99(FIG. 4F).

Example 3

This Example demonstrates the presence of the identified biomarkers intumor tissue.

Tumor and matched adjacent normal tissues were pulverized by cryogenicgrinding (Cryomill®, Retsch GmbH, Haan, Germany) using a 5 mm stainlesssteel ball. Average sample weight was 15 mg. A monophasic mixture ofice-cold chloroform:methanol:water (2:5:2, v:v:v) was used forextraction. Samples were centrifuged at 14,000×g for 15 minutes at 4°C., and reconstituted in 70% aqueous acetonitrile before they wereinjected onto the Xevo TQMS system. Creatine riboside andN-acetylneuraminic acid were significantly more abundant in tumor tissuecompared to adjacent normal tissue, as assessed in 48 stage Iadenocarcinoma and squamous cell carcinoma patients (FIG. 4D). Creatinewas also elevated in the tumor compared to adjacent normal tissue, andcorrelates with creatine riboside (FIG. 7).

Example 4

This Example illustrates an assessment of the contribution of eachmetabolite to lung cancer.

To assess the contribution of each metabolite to lung cancer risk, weperformed logistic regression in all and in early stage I-II cases (FIG.8A), adjusting for race, gender, interview year, smoking status, packyears and urine collection. Logistic regression was performed in STATA(Stata Statistical Software Release 11.2, College Station, Tex.).P-values were corrected for multiple hypotheses testing using falsediscovery rate method by Benjamini and Hochberg (Benjamini Y, HochbergY. Controlling the False Discovery Rate: A Practical and PowerfulApproach to Multiple Testing. Journal of the Royal Statistical SocietySeries B (Methodological) 1995; 57:11.). Of note, associations areindependent of histology (data not shown). Additionally, the number ofcigarettes per day is not associated with the levels of the top fourbiomarkers in either the cases or the controls (FIG. 9). However,N-acetylneuraminic acid levels do show some diurnal variation (FIG. 10),and therefore all analyses were adjusted for the time of day urine wascollected. ROC analysis resulted in areas under the curve (AUC) rangingfrom 0.63 to 0.76 for all cases, and 0.59 to 0.70 for early stage cases(FIG. 8B), using individual metabolites. Models using creatine ribosideor all four biomarkers in all and in early stage cases are significantlymore predictive (P<0.00001) than models using the other 3 metabolitesindividually.

Example 5

This Example illustrates an assessment of the association between levelsof biomarkers of the present invention and prognosis.

Survival analyses were performed in SAS Enterprise Guide, version 4.2(SAS Institute Inc.) and all reported P values were two-sided. Signalabundances were dichotomized into binary variables using a tertilecutoff, based on the distribution of the abundances of the healthycontrols. Cox models with left truncation were performed to account forthe lag time, up to two years, between diagnosis and urine collectiondates. Multivariate Cox models were adjusted for urine collection time,histology, stage, race, gender, interview year, pack years and smokingstatus. The proportional hazards assumption was tested and if not met,the hazard ratio function was calculated separately before and after agiven time point. This cutoff was determined by the time at which thesurvival curves started to diverge/converge and by ensuring that the 0coefficients of the signal-time term before and after were no longersignificant. As shown below in Table 4, after adjusting for gender,race, stage, histology, smoking status, pack years, interview year, andurine collection time, high levels of cortisol sulfate (HR=1.49(P=0.003), creatine riboside (HR=1.76 (P=0.0003) in the first 45months), N-acetylneuraminic acid (HR=1.57 (P=0.02) in the first 15months) and 561+(HR=1.97 (P<0.00001) in the first 20 months) areassociated with worse survival (also see FIG. 11A for Kaplan-Meierplots).

TABLE 4 Cox proportional hazards regression results are depicted forboth all cases, and stage I-II cases in the training set. UnivariateMultivariate* Signal HR (95% CI) P FDR^(†) HR (95% CI) P FDR^(†) AllCases (N = 469) N-acetylneuraminic acid <=15 months 1.74 (1.22-2.48)0.002 0.06 1.57 (1.07-2.29) 0.02 0.20  >15 months 1.14 (0.82-1.57) 0.441.26 (0.90-1.78) 0.19 Cortisol sulfate 1.53 (1.21-1.94) 0.0004 0.01 1.49(1.15-1.94) 0.003 0.03 Creatine riboside <=45 months 2.05 (1.54-2.71)<0.0001 0.0005 1.76 (1.29-2.39) 0.0003 0.003  >45 months 0.86(0.38-1.95) 0.72 0.79 (0.34-0.85) 0.59 561+ <=20 months 2.32 (1.70-3.15)<0.0001 0.001 1.97 (1.41-2.75) <0.0001 0.003  >20 months 1.05(0.70-1.55) 0.83 0.88 (0.57-2.75) 0.54 Stage I-II Cases (N = 213)N-acetylneuraminic acid 0.70 (0.41-1.19) 0.18 0.89 0.64 (0.36-1.12) 0.120.81 Cortisol sulfate 1.45 (0.90-2.32) 0.12 0.89 1.43 (0.87-2.35) 0.160.81 Creatine riboside 1.78 (1.08-2.93) 0.02 0.81 1.83 (1.08-3.09) 0.030.64 561+ <=15 months  7.83 (2.23-27.51) 0.001 0.60  9.33 (2.62-33.23)0.0006 0.20 >15 months 0.83 (0.45-1.52) 0.54 1.02 (0.54-1.95) 0.95*Adjusted for gender, race, stage (unless stratified), histology,smoking status, pack years, interview year and urine collection time^(†)False discovery rate (FDR) based on Benjamini and Hochberg

In early stage cases, creatine riboside (HR=1.83 (P=0.03)) and561+(HR=9.33 (P=0.0006) in the first 15 months) are associated withsurvival, independent of aforementioned clinical variables (Table 4,FIG. 11B). Importantly, the combination of these metabolites and theirassociations with survival demonstrates an independent and additiveeffect (FIG. 11C). In advanced stages (III-IV), creatine ribosideremains associated with survival, in addition to N-acetylneuraminicacid, and cortisol sulfate (FIG. 12). As shown below in Table 5,stratification by race highlights cortisol sulfate as being moststrongly associated with survival in African Americans.

TABLE 5 Associations with survival in the training set, stratified byrace. All Cases All Cases (N = 469) Univariate Multivariate* Signal HR(95% CI) P HR (95% CI) P N-acetyl neuraminic acid <=15 months 1.74(1.22-2.48) 0.002 1.57 (1.07-2.29) 0.02 >15 months 1.14 (0.82-1.57) 0.441.26 (0.90-1.78) 0.19 Cortisol sulfate 1.53 (1.21-1.94) 0.0004 1.49(1.15-1.94) 0.003 Creatine riboside <=45 months 2.05 (1.54-2.71) <0.00011.76 (1.29-2.39) 0.0003 >45 months 0.86 (0.38-1.95) 0.72 0.79(0.34-0.85) 0.59 561+ <=20 months 2.32 (1.70-3.15) <0.0001 1.97(1.41-2.75) <0.0001 >20 months 1.05 (0.70-1.55) 0.83 0.88 (0.57-2.75)0.54 Caucasians All Caucasians (N = 342) Univariate Multivariate* SignalHR (95% CI) P HR (95% CI) P N-acetylneuraminic acid <=15 months 1.77(1.23-2.56) 0.002 1.22 (0.84-1.69) 0.23 >15 months 0.73 (0.45-1.17) 0.190.78 (0.28-2.21) 0.64 Cortisol sulfate 1.22 (0.92-1.62) 0.166 1.23(0.90-1.67) 0.20 Creatine riboside <=45 months 1.97 (1.42-2.73) <0.00011.66 (1.16-2.37) 0.005 >45 months 0.95 (0.39-2.34) 0.92 0.84 (0.34-2.09)0.71 561+ <=20 months 1.89 (1.31-2.72) 0.0007 1.64 (1.10-2.45) 0.02 >20months 1.09 (0.67-1.76) 0.72 0.96 (0.58-1.62) 0.89 African Americans AllAfrican Americans (N = 127) Univariate Multivariate* Signal HR (95% CI)P HR (95% CI) P N-acetylneuraminic acid 1.66 (1.07-2.57) 0.02 1.29(0.73-2.28) 0.38 Cortisol sulfate 2.80 (1.77-4.42) <0.0001 3.89(2.08-7.28) <0.0001 Creatine riboside 1.89 (1.10-3.27) 0.02 1.40(0.72-2.72) 0.33 561+ <=20 months 4.03 (2.07-7.84) <0.0001  4.69(2.12-10.40) 0.0001 >20 months 0.87 (0.43-1.78) 0.70 0.92 (0.40-2.12)0.85 *Adjusted for gender, race (unless stratified), stage, histology,smoking status, pack years, interview year and urine collection time

Associations were confirmed in the quantitation set comprising 198samples (FIG. 13).

Example 6

This Example compares the levels of biomarkers of the present inventionpresent in colon tumor tissue with the levels observed in non-canceroustissue.

Global metabolomics analysis was conducted on 40 tumor and adjacentnon-tumor tissue samples (Table 6).

TABLE 6 Colon cancer tissue set characteristics. Tumor/Adjacent NormalPairs (N = 40) Age (mean = 66.8) >mean 24 <=mean 16 Histologyadenocarcinoma 31 mucinous adenocarcinoma 7 squamous cell carcinoma 1carcinoma 1 Gender Female 21 Male 19 Stage I-II 22 III-IV 18

Average sample weight was 10 mg. Each tissue sample was processed twice,the first method using Cryogenic grinding, and the second method usingtissue homogenization at room temperature. The first method consisted ofcryogenic pulverization of tissue at ˜−200° C. (Cryomill®, Retsch GmbH,Haan, Germany) using a 5 mm stainless steel ball. The second methodconsisted of tissue homogenization at room temperature using Precellyshomogenizer (Bertin Technologies) and zirconium oxide beads (2.8 mm).Both methods were investigated as a form of a technical validation. Inaddition, the effect of variations in temperature during the extractionprocess on the stability of the metabolites of interest, creatineriboside and N-acetylneuraminic acid (NANA), was also investigated.After homogenization by both methods, metabolites were extracted asfollows: a monophasic mixture of ice-cold chloroform:methanol:water(2:5:2, v:v:v) was used. Samples were centrifuged at 14,000×g for 15minutes at 4° C., dried down using SpeedVac and reconstituted in 70%aqueous acetonitrile before they were injected onto the Xevo TQMSsystem. For the quality control purposes, blank, pooled and samplescontaining a cocktail of internal standards were included. A clusteringof the quality control samples separately from the tissue samplesindicates successful chromatography (FIG. 15). All samples were run on aquadrupole time-of-flight (QTOF) mass spectrometer (Premier, Waters), inpositive (ESI+) and negative (ESI−) electrospray ionization modes, usinghydrophilic interaction chromatography (HILIC) columns (Acquity UPLC BEHAmide 1.7 μm 50×2.1 mm) for a better separation of polar compounds. Thelevels of creatine riboside and NANA, which were previously found to besignificantly upregulated in the urine and tumor tissue of lung cancerpatients, were investigated and found to be upregulated in the colontumor compared to adjacent non-tumor tissue (FIG. 16, reported P-valuesare based on the matched t-test). These findings indicate that these twometabolites are universally applicable as cancer markers.

Example 7

This Example examines the ability of the levels of biomarkers of thepresent invention in urine to diagnose and predict the prognosis of lungcancer.

Urine from 98 liver cancer cases frequency matched on age, gender andrace to a 100 population controls, as well as 99 prostate cancer casesfrequency matched on age and gender to 98 population controls wasexamined. Briefly, 2504, of urine was diluted 1:1 using 50% acetonitrilein water containing chloropropamide and aminopimelic acid as internalstandards, vortexed briefly and spun for at 4° C. at 14,000×g 15minutes. Samples were then chromatographed on a 50×2.1 mm Acquity BEH1.7 μm C18 column using an ACQUITY UPLC™ system (WATERS®). MRMtransitions were monitored using a XEVO®TQMS (WATERS®). In addition,samples were analyzed using hydrophilic interaction chromatography(HILIC) columns (ACQUITY UPLC™ BEH Amide 1.7 μm 50×2.1 mm) for thequantitation of creatine riboside and NANA. HILIC columns improveretention, separation, and detection of highly polar metabolites. Allsamples were normalized to creatinine levels to control for kidneyfunction.

The results of these studies showed that high levels of all fourmetabolites, creatine riboside, cortisol sulfate, N-acetylneuraminicacid and 561+ were associated with lung cancer status (diagnosis) in theliver cases when compared to matched population controls (FIG. 17, top)after adjustment for potential confounding factors, race, gender,interview year, smoking status and pack years. In prostate cancer, highlevels of cortisol sulfate are associated with lung cancer status(diagnosis) after adjustment for potential confounding factors, race,interview year, smoking status and pack years, while high levels ofcreatine riboside are borderline significant (P=0.08) (FIG. 17, bottom).Due to a limited number of cases and controls in this study, it ishighly probable that we do not have the power to detect theseassociations in prostate cancer in the multivariate analysis afteradjusting for potential confounders. However, odds ratios (ORs) show thesame direction of the association as in lung cancer where thesebiomarkers were initially discovered. Furthermore, Wilcoxon analysis(FIG. 18) shows that all four metabolites are significantly (P<0.05)elevated in both liver and prostate cancer cases when compared to theirmatched population controls. The data presented herein indicates thatthe levels of creatine riboside, cortisol sulfate, N-acetylneuraminicacid and metabolite 561+ in the urine are useful in diagnosing cancer.

What is claimed is:
 1. A method for detecting the presence of cancer,the method comprising a determining step selected from the groupconsisting of: a) determining the level of at least two compoundsselected from the group consisting of creatine riboside, metabolite561+, cortisol sulfate and N-acetylneuraminic acid in a sample obtainedfrom an individual; and, b) determining the level of one or morecompounds selected from the group consisting of creatine riboside andmetabolite 561+, in a sample from an individual; wherein elevated levelsof the at least two compounds in step a), or elevated levels of creatineriboside and/or metabolite 561+ in step b) indicates the presence ofcancer.
 2. The method of claim 1, wherein the method comprisesdetermining the level of at least three compounds selected from thegroup consisting of creatine riboside, metabolite 561+, cortisol sulfateand N-acetylneuraminic acid in a sample obtained from an individual,wherein elevated levels of the at least three compounds indicates thepresence of cancer
 3. The method of claim 1, wherein the methodcomprises determining the level of creatine riboside, metabolite 561+,cortisol sulfate and N-acetylneuraminic acid in a sample obtained froman individual, wherein elevated levels of all four compounds indicatesthe presence of cancer.
 4. The method of claim 1, wherein the sample isbody tissue.
 5. The method of claim 1, wherein the sample is a bodyfluid.
 6. The method of claim 5, wherein the body fluid is selected fromthe group consisting of blood, plasma and serum.
 7. The method of claim5, wherein the body fluid is urine.
 8. The method of claim 1, whereinthe cancer is lung cancer.
 9. The method of claim 1, wherein the cancercomprises adenocarcinoma or squamous cell carcinoma. 10-16. (canceled)17. A method for identifying an individual as having lung cancer, themethod comprising a determining step selected from the group consistingof: a) determining the level of cortisol sulfate in a body fluidobtained from an individual; and, b) determining the level ofN-acetylneuraminic acid in urine from an individual; and identifying theindividual as having lung cancer if the level of cortisol sulfate in thebody fluid is elevated or if the urinary N-acetylneuraminic acid levelis elevated. 18-19. (canceled)
 20. The method of claim 17, wherein thebody fluid of a) is selected from the group consisting of blood, plasmaand serum.
 21. The method of claim 20, wherein the body fluid is urine.22. The method of claim 17, wherein the cancer comprises adenocarcinomaor squamous cell carcinoma. 23-29. (canceled)
 30. The method of claim 1,wherein if the presence of cancer is detected, the method furthercomprises: c) administering a cancer treatment to the patient; d) at aperiod of time following administration of the treatment, determiningthe level of: i) at least two compounds selected from the groupconsisting of creatine riboside, metabolite 561+, cortisol sulfate andN-acetylneuraminic acid in a sample obtained from the individual; or,ii) one or more compounds selected from the group consisting of creatineriboside and metabolite 561+, in a sample from the individual; to obtaina post-treatment level of the one or more biomarkers; and, e) comparingthe pre-treatment and post-treatment biomarker levels to determine theefficacy of the treatment.
 31. A method for predicting the prognosis ofan individual having cancer, the method comprising determining the levelof at least one biomarker selected from the group consisting of creatineriboside, cortisol sulfate, metabolite 561+ and N-acetylneuraminic acidin a sample of body fluid from the individual, and predicting theprognosis of the individual based on an elevated level of the at leastone biomarker.
 32. The method of claim 31, wherein the body fluid isselected from the group consisting of urine, blood, plasma and serum.33. The method of claim 31, wherein the cancer is lung cancer.
 34. Themethod of claim 31, wherein the cancer comprises adenocarcinoma orsquamous cell carcinoma.
 35. The method of claim 31, wherein the methodcomprises determining the levels of at least two biomarkers selectedfrom the group consisting of creatine riboside, cortisol sulfate,metabolite 561+ and N-acetylneuraminic acid in a sample of body fluidfrom the individual.
 36. The method of claim 31, wherein the methodcomprises determining the levels of creatine riboside, cortisol sulfate,metabolite 561+ and N-acetylneuraminic acid in a sample of body fluidfrom the individual.